#Custom Data Extraction services

[datadwipservice]

Streamline your business operations and unlock the full potential of your data with our Data Management Solutions in the USA. We offer end-to-end data management services, including data integration, cleansing, storage, governance, and analytics, tailored to meet the unique needs of your organization.

[forage-ai]

The Role of Custom Web Data Extraction: Enhancing Business Intelligence and Competitive Advantage

Your off-the-shelf scraping tool worked perfectly last month. Then your target website updated their layout. Everything broke.

Your data pipeline stopped. Your competitive intelligence disappeared. Your team scrambled to fix scripts that couldn’t handle the new structure.

This scenario repeats across thousands of businesses using off-the-shelf extraction tools. Here’s the problem: 89% of leaders recognize web data’s importance. But standardized solutions fail when websites fight back with anti-bot defenses, dynamic content, or simple redesigns.

Custom extraction solves these problems. AI-powered systems see websites like humans do. They adapt automatically when things change.

This article reveals how custom web data extraction delivers reliable intelligence where off-the-shelf tools fail. You’ll discover why tailored solutions outperform one-size-fits-all approaches. You’ll also get to see a detailed industry-specific guide showing how business leaders solve their most complex data challenges.

Beyond Basic Scraping: What Makes Custom Web Data Extraction Different

Basic tools rely on rigid scripts. They expect websites to stay frozen in time. That’s simply not how the modern web works.

Today’s websites use sophisticated blocking techniques:

Rotating CAPTCHA challenges.

Browser fingerprinting.

IP rate limiting.

Complex JavaScript frameworks that render content client-side.

Custom solutions overcome these barriers. They use advanced capabilities you won’t find in basic tools.

Here’s what sets custom web data extraction apart:

Tailored architecture designed for your specific needs and target sources.

AI-powered browsers that render pages exactly as humans see them.

Intelligent IP rotation through thousands of addresses to avoid detection.

Automatic adaptation when target websites change their structure.

Enterprise-grade scale monitoring millions of pages across thousands of sources.

Basic tools might handle dozens of sites with hundreds of results. But they require constant babysitting from your team. Every website redesign breaks your scripts. Every new blocking technique stops your data flow.

On the other hand, enterprise-grade custom solutions monitor thousands of sources simultaneously. Their scrapers extract millions of data points with pinpoint accuracy and adapt automatically when sites change structure.

But here’s what really matters: intelligent data processing.

Raw scraped data is messy and inconsistent. Tailored solutions transform this chaos into structured intelligence by:

Cleaning and standardizing information automatically.

Matching products across different retailers despite varying naming conventions.

Identifying and flagging anomalies that could indicate data quality issues.

Structuring unstructured data into analysis-ready formats.

Industry research reveals that the technical barriers are real. 82% of organizations need help overcoming data collection challenges:

55% face IP blocking.

52% struggle with CAPTCHAs.

56% deal with dynamic content that traditional tools can’t handle.

This is why sophisticated businesses partner with experienced providers like Forage AI. We’ve perfected these capabilities over decades of experience and provide you with enterprise-grade capabilities without the headaches of maintaining complex infrastructure.

Now that you understand what makes custom extraction powerful, let’s see how this capability transforms the core business functions that drive competitive advantage.

Transforming Business Intelligence Across Key Functions

Custom web data extraction doesn’t just collect information. It revolutionizes how organizations understand their markets, customers, and competitive landscape.

Here’s how it transforms three critical business intelligence areas:

Real-Time Competitive Analysis

Forget checking competitor websites once a week. Custom extraction provides continuous competitive surveillance. It captures changes the moment they happen.

Your system monitors:

Pricing changes and product launches across competitor portfolios.

Executive appointments and organizational restructuring at target companies.

Regulatory filings and compliance updates from government sources.

Market expansion and strategic partnerships across your industry.

The competitive advantage:

Shift from reactive to proactive strategic positioning.

Respond within hours instead of days when competitors make a move.

Anticipate market shifts before other players spot them.

Position strategically based on live competitive intelligence.

Customer Intelligence & Market Insights

Understanding your customers means looking beyond your own data. You need to see how they behave across the entire market.

Custom extraction aggregates customer sentiment, preferences, and feedback from every relevant touchpoint online.

Comprehensive customer intelligence includes:

Review patterns across all major platforms to identify valued features.

Social media conversations to spot emerging trends before mainstream awareness.

Forum discussions to understand unmet needs representing new opportunities.

Purchase behavior signals across competitor platforms and review sites.

Strategic insights you gain:

Why customers choose competitors over you.

What actually drives their purchase decisions.

How their preferences evolve over time.

Which features and benefits resonate most strongly with your target market.

Operational Intelligence

Smart organizations use web data to optimize operations beyond marketing and sales. Custom extraction provides the external intelligence that makes internal operations more efficient and strategic.

Supply chain optimization through:

Supplier monitoring of websites, industry news, and regulatory announcements.

Commodity price tracking and shipping delay alerts.

Geopolitical event monitoring that could affect procurement strategies.

Risk management enhancement via:

Early warning signals from news sources and regulatory sites.

Compliance issue identification before they impact operations.

Reputation threat monitoring across digital channels.

Strategic planning support including:

Competitor expansion intelligence and market opportunity identification.

Industry trend analysis that shapes future strategy.

Market condition assessment for long-term decision-making.

This operational intelligence enables informed strategic planning. You gain comprehensive context for critical business decisions.

With these transformed business functions providing superior market intelligence, you’re positioned to create sustainable competitive advantages. But how exactly does this intelligence translate into lasting business benefits? Let’s examine the specific advantages that compound over time.

Creating Sustainable Competitive Advantages

The real power of custom web data extraction isn’t just better information. It’s the systematic advantages that compound over time. Your organization becomes increasingly difficult for competitors to match.

Speed and Agility

Research shows that 73% of organizations achieve quicker decision-making through systematic web data collection. But speed isn’t just about faster decisions. It’s about being first to market opportunities.

Immediate competitive benefits:

Capitalize on competitor pricing errors immediately rather than discovering them days later.

Adjust strategy while competitors are still gathering information.

Position yourself for new opportunities while others are still analyzing.

Compounding speed advantages:

Each quick response strengthens your market position. Customers associate your brand with market leadership. New opportunities become easier to capture.

Consider dynamic pricing strategies. They adjust in real-time based on competitor actions, inventory levels, and demand signals. Organizations using this approach report revenue increases of 5-25% compared to static pricing models.

Complete Market Coverage

While competitors rely on off-the-shelf tools that have limited coverage, custom extraction provides 360-degree market visibility. Industry research indicates that 98% of organizations need more data of at least one type. Tailored solutions eliminate this limitation entirely.

Your monitoring advantage includes:

Direct competitors and adjacent markets that could affect your business.

Pricing, inventory, promotions plus customer sentiment and regulatory changes.

Primary markets plus possibilities of international expansion.

Current conditions and emerging trends before they become obvious.

The scale difference is striking. Simple extraction tools can only handle dozens of products from a few sites before breaking down. Custom extraction monitors thousands of sources continuously with high accuracy. This creates market intelligence that’s simply impossible with off-the-shelf solutions.

Predictive Analytics Capability

With comprehensive, real-time data flowing systematically, you can build predictive capabilities. You anticipate market changes rather than just responding to them.

This is where Forage AI’s expertise becomes critical. We process data from 500M+ websites with AI-powered techniques, transforming raw information into strategic insights. 53% of organizations use public web data specifically to build the AI models that power these predictive insights.

Predictive intelligence detects:

Customer churn signals weeks before accounts show obvious warning signs.

Supply chain disruptions preventing inventory shortages before they impact operations.

Fraud detection patterns identifying suspicious activities before financial losses occur.

Lead scoring optimization predicting which prospects convert before competitors spot them.

The combination of speed, coverage, and prediction creates competitive advantages that are difficult for rivals to replicate. They’d need to invest in similar systematic data capabilities to match your market intelligence. By that time, you’ve gained additional advantages through earlier implementation.

These competitive benefits become even more powerful when applied to specific industry challenges. Let’s take a look at how different sectors leverage these capabilities for measurable ROI.

Industry-Specific Applications That Drive ROI

Different industries face unique competitive challenges. Custom web data extraction solves these in specific, measurable ways.

E-commerce & Retail

Retail operates in the most price-transparent market in history. 75% of retail organizations collect market data systematically while 51% use it specifically for brand health monitoring across multiple channels.

But here’s what sets custom extraction apart from basic extraction tools:

Visual Intelligence Engines: Extract and analyze product images across 1000+ competitor sites to identify color trends, style patterns, and merchandising strategies. Spot emerging visual trends 48 hours before they go mainstream by handling JavaScript-heavy product galleries that load dynamically as users scroll – something basic tools simply can’t manage.

Review Feature Mining: Go beyond sentiment scores. Extract unstructured review data to identify specific product features customers mention that aren’t in your specs. When customers repeatedly request “pockets” in competitor dress reviews, you’ll know before your next design cycle.

Micro-Influencer Discovery: Scrape social media platforms to find micro-influencers already organically mentioning your product category. Identify authentic voices with engaged audiences before they’re on anyone’s radar.

Stock Pattern Prediction: Monitor availability patterns across competitor sites to predict stockouts 7-10 days in advance. This isn’t just checking “in stock” labels – it’s analyzing restocking frequencies, quantity limits, and shipping delays.

Financial Services

Financial institutions face unique challenges around risk assessment, regulatory compliance, and market intelligence.

Custom extraction delivers capabilities impossible with standard tools:

Alternative Data Signals: Extract job postings, online company reviews, and web traffic patterns to assess company health 90 days before earnings reports. When a tech company suddenly posts 50 new sales positions while their engineering hiring freezes, you’ll spot the pivot early.

Multi-Language Regulatory Intelligence: Monitor 200+ regulatory websites across dozens of languages simultaneously for policy changes. Detect subtle shifts in compliance requirements weeks before official translations appear. This requires sophisticated language processing beyond basic translation.

ESG Risk Detection: Scrape news sites, NGO reports, and social media for real-time Environmental, Social, and Governance risk indicators. Identify supply chain controversies or environmental violations before they impact investment portfolios.

High-Frequency Data Extraction: Handle encrypted financial documents and real-time feeds from trading platforms. Process complex data structures that update milliseconds apart while maintaining accuracy.

Healthcare

Healthcare organizations need extraction capabilities that handle complex medical data and compliance requirements:

Clinical Trial Competition Intelligence: Extract real-time patient enrollment numbers and protocol changes from ClinicalTrials.gov and competitor sites. Know when rivals struggle with recruitment or modify trial endpoints. This means parsing complex medical documents and research papers.

Physician Opinion Tracking: Monitor medical forums and conference abstracts for emerging treatment preferences. Detect when specialists start discussing off-label uses or combination therapies 6 months before publication.

Drug Shortage Prediction: Combine Food and Drug Administration databases with pharmacy inventory signals to predict shortages 2-3 weeks early. Extract data from multiple formats while handling medical terminology variations.

Patient Journey Mapping: Analyze anonymized patient experiences from health forums to understand real treatment pathways. Navigate HIPAA-compliant extraction while capturing meaningful insights.

Manufacturing

Manufacturing requires extraction solutions that handle technical complexity across global supply chains:

Component Crisis Detection: Monitor 500+ distributor websites globally for lead time changes on critical components. Detect when a key supplier extends delivery from 8 to 12 weeks before it impacts your production line.

Patent Innovation Tracking: Extract and analyze competitor patent filings to identify technology directions 18 months before product launches. Parse technical specifications and CAD file references to understand true innovation patterns.

Quality Signal Detection: Mine consumer forums and review sites for early product defect patterns. Identify quality issues weeks before they escalate to recalls. This requires understanding technical language across multiple industries.

Sustainability Compliance Monitoring: Extract supplier ESG certifications, audit results, and environmental data from diverse sources. Track your entire supply chain’s compliance status in real-time across different reporting standards.

The Bottom Line: Measurable Impact Across Your Business

When you add it all up, custom web data extraction delivers three types of measurable value:

Immediate efficiency gains through automated intelligence gathering, reducing data processing time by 30-40% while improving decision speed and accuracy.

Revenue acceleration via dynamic pricing optimization (5-25% increases), market timing advantages, and strategic positioning based on comprehensive market understanding.

Risk reduction through early warning systems that spot threats before they impact operations, enabling proactive responses rather than costly reactive measures.

Organizations implementing these capabilities systematically are 57% more likely to expect significant revenue growth. The compound effect means early adopters gain advantages that become increasingly difficult for competitors to match.

These industry applications prove a key point. Sophisticated web data extraction isn’t just a technical capability. It’s a strategic business tool that drives measurable edge across diverse sectors and use cases.

Conclusion: Custom Data Extraction as Competitive Necessity

The evidence is clear. Organizations that systematically leverage web data consistently outperform those relying on manual methods or standard extraction techniques.

89% of business leaders recognize data’s importance. But only those implementing custom extraction solutions capture its full competitive potential.

This isn’t about having better tools. It’s about fundamentally transforming how you understand and respond to market dynamics. Custom web data extraction provides the systematic intelligence foundation that modern competitive strategy requires.

The question isn’t whether to invest in these capabilities. It’s how quickly you can implement them before competitors gain similar advantages.

Ready to stop guessing and start knowing? Contact Forage AI to discover how custom web data extraction can transform your competitive positioning and business intelligence capabilities.

[datascraping001]

Google Search Results Data Scraping

Google Search Results Data Scraping

Harness the Power of Information with Google Search Results Data Scraping Services by DataScrapingServices.com. In the digital age, information is king. For businesses, researchers, and marketing professionals, the ability to access and analyze data from Google search results can be a game-changer. However, manually sifting through search results to gather relevant data is not only time-consuming but also inefficient. DataScrapingServices.com offers cutting-edge Google Search Results Data Scraping services, enabling you to efficiently extract valuable information and transform it into actionable insights.

The vast amount of information available through Google search results can provide invaluable insights into market trends, competitor activities, customer behavior, and more. Whether you need data for SEO analysis, market research, or competitive intelligence, DataScrapingServices.com offers comprehensive data scraping services tailored to meet your specific needs. Our advanced scraping technology ensures you get accurate and up-to-date data, helping you stay ahead in your industry.

List of Data Fields

Our Google Search Results Data Scraping services can extract a wide range of data fields, ensuring you have all the information you need:

-Business Name: The name of the business or entity featured in the search result.

- URL: The web address of the search result.

- Website: The primary website of the business or entity.

- Phone Number: Contact phone number of the business.

- Email Address: Contact email address of the business.

 - Physical Address: The street address, city, state, and ZIP code of the business.

- Business Hours: Business operating hours

- Ratings and Reviews: Customer ratings and reviews for the business.

- Google Maps Link: Link to the business’s location on Google Maps.

- Social Media Profiles: LinkedIn, Twitter, Facebook

These data fields provide a comprehensive overview of the information available from Google search results, enabling businesses to gain valuable insights and make informed decisions.

Benefits of Google Search Results Data Scraping

1. Enhanced SEO Strategy

Understanding how your website ranks for specific keywords and phrases is crucial for effective SEO. Our data scraping services provide detailed insights into your current rankings, allowing you to identify opportunities for optimization and stay ahead of your competitors.

2. Competitive Analysis

Track your competitors’ online presence and strategies by analyzing their rankings, backlinks, and domain authority. This information helps you understand their strengths and weaknesses, enabling you to adjust your strategies accordingly.

3. Market Research

Access to comprehensive search result data allows you to identify trends, preferences, and behavior patterns in your target market. This information is invaluable for product development, marketing campaigns, and business strategy planning.

4. Content Development

By analyzing top-performing content in search results, you can gain insights into what types of content resonate with your audience. This helps you create more effective and engaging content that drives traffic and conversions.

5. Efficiency and Accuracy

Our automated scraping services ensure you get accurate and up-to-date data quickly, saving you time and resources.

Best Google Data Scraping Services

Scraping Google Business Reviews

Extract Restaurant Data From Google Maps

Google My Business Data Scraping

Google Shopping Products Scraping

Google News Extraction Services

Scrape Data From Google Maps

Google News Headline Extraction   

Google Maps Data Scraping Services

Google Map Businesses Data Scraping

Google Business Reviews Extraction

Best Google Search Results Data Scraping Services in USA

Dallas, Portland, Los Angeles, Virginia Beach, Fort Wichita, Nashville, Long Beach, Raleigh, Boston, Austin, San Antonio, Philadelphia, Indianapolis, Orlando, San Diego, Houston, Worth, Jacksonville, New Orleans, Columbus, Kansas City, Sacramento, San Francisco, Omaha, Honolulu, Washington, Colorado, Chicago, Arlington, Denver, El Paso, Miami, Louisville, Albuquerque, Tulsa, Springs, Bakersfield, Milwaukee, Memphis, Oklahoma City, Atlanta, Seattle, Las Vegas, San Jose, Tucson and New York.

Conclusion

In today’s data-driven world, having access to detailed and accurate information from Google search results can give your business a significant edge. DataScrapingServices.com offers professional Google Search Results Data Scraping services designed to meet your unique needs. Whether you’re looking to enhance your SEO strategy, conduct market research, or gain competitive intelligence, our services provide the comprehensive data you need to succeed. Contact us at info@datascrapingservices.com today to learn how our data scraping solutions can transform your business strategy and drive growth.

Website: Datascrapingservices.com

Email: info@datascrapingservices.com

[mostlysignssomeportents]

There Were Always Enshittifiers

I'm on a 20+ city book tour for my new novel PICKS AND SHOVELS. Catch me in DC TONIGHT (Mar 4), and in RICHMOND TOMORROW (Mar 5). More tour dates here. Mail-order signed copies from LA's Diesel Books.

My latest Locus column is "There Were Always Enshittifiers." It's a history of personal computing and networked communications that traces the earliest days of the battle for computers as tools of liberation and computers as tools for surveillance, control and extraction:

https://locusmag.com/2025/03/commentary-cory-doctorow-there-were-always-enshittifiers/

The occasion for this piece is the publication of my latest Martin Hench novel, a standalone book set in the early 1980s called "Picks and Shovels":

https://us.macmillan.com/books/9781250865908/picksandshovels

The MacGuffin of Picks and Shovels is a "weird PC" company called Fidelity Computing, owned by a Mormon bishop, a Catholic priest, and an orthodox rabbi. It sounds like the setup for a joke, but the punchline is deadly serious: Fidelity Computing is a pyramid selling cult that preys on the trust and fellowship of faith groups to sell the dreadful Fidelity 3000 PC and its ghastly peripherals.

You see, Fidelity's products are booby-trapped. It's not merely that they ship with programs whose data-files can't be read by apps on any other system – that's just table stakes. Fidelity's got a whole bag of tricks up its sleeve – for example, it deliberately damages a specific sector on every floppy disk it ships. The drivers for its floppy drive initialize any read or write operation by checking to see if that sector can be read. If it can, the computer refuses to recognize the disk. This lets the Reverend Sirs (as Fidelity's owners style themselves) run a racket where they sell these deliberately damaged floppies at a 500% markup, because regular floppies won't work on the systems they lure their parishioners into buying.

Or take the Fidelity printer: it's just a rebadged Oki­data ML-80, the workhorse tractor feed printer that led the market for years. But before Fidelity ships this printer to its customers, they fit it with new tractor feed sprockets whose pins are slightly more widely spaced than the standard 0.5" holes on the paper you can buy in any stationery store. That way, Fidelity can force its customers to buy the custom paper that they exclusively peddle – again, at a massive markup.

Needless to say, printing with these wider sprocket holes causes frequent jams and puts a serious strain on the printer's motors, causing them to burn out at a high rate. That's great news – for Fidelity Computing. It means they get to sell you more overpriced paper so you can reprint the jobs ruined by jams, and they can also sell you their high-priced, exclusive repair services when your printer's motors quit.

Perhaps you're thinking, "OK, but I can just buy a normal Okidata printer and use regular, cheap paper, right?" Sorry, the Reverend Sirs are way ahead of you: they've reversed the pinouts on their printers' serial ports, and a normal printer won't be able to talk to your Fidelity 3000.

If all of this sounds familiar, it's because these are the paleolithic ancestors of today's high-tech lock-in scams, from HP's $10,000/gallon ink to Apple and Google's mobile app stores, which cream a 30% commission off of every dollar collected by an app maker. What's more, these ancient, weird misfeatures have their origins in the true history of computing, which was obsessed with making the elusive, copy-proof floppy disk.

This Quixotic enterprise got started in earnest with Bill Gates' notorious 1976 "open letter to hobbyists" in which the young Gates furiously scolds the community of early computer hackers for its scientific ethic of publishing, sharing and improving the code that they all wrote:

https://en.wikipedia.org/wiki/An_Open_Letter_to_Hobbyists

Gates had recently cloned the BASIC programming language for the popular Altair computer. For Gates, his act of copying was part of the legitimate progress of technology, while the copying of his colleagues, who duplicated Gates' Altair BASIC, was a shameless act of piracy, destined to destroy the nascent computing industry:

As the majority of hobbyists must be aware, most of you steal your software. Hardware must be paid for, but software is something to share. Who cares if the people who worked on it get paid?

Needless to say, Gates didn't offer a royalty to John Kemeny and Thomas Kurtz, the programmers who'd invented BASIC at Dartmouth College in 1963. For Gates – and his intellectual progeny – the formula was simple: "When I copy you, that's progress. When you copy me, that's piracy." Every pirate wants to be an admiral.

For would-be ex-pirate admirals, Gates's ideology was seductive. There was just one fly in the ointment: computers operate by copying. The only way a computer can run a program is to copy it into memory – just as the only way your phone can stream a video is to download it to its RAM ("streaming" is a consensus hallucination – every stream is a download, and it has to be, because the internet is a data-transmission network, not a cunning system of tubes and mirrors that can make a picture appear on your screen without transmitting the file that contains that image).

Gripped by this enshittificatory impulse, the computer industry threw itself headfirst into the project of creating copy-proof data, a project about as practical as making water that's not wet. That weird gimmick where Fidelity floppy disks were deliberately damaged at the factory so the OS could distinguish between its expensive disks and the generic ones you bought at the office supply place? It's a lightly fictionalized version of the copy-protection system deployed by Visicalc, a move that was later publicly repudiated by Visicalc co-founder Dan Bricklin, who lamented that it confounded his efforts to preserve his software on modern systems and recover the millions of data-files that Visicalc users created:

http://www.bricklin.com/robfuture.htm

The copy-protection industry ran on equal parts secrecy and overblown sales claims about its products' efficacy. As a result, much of the story of this doomed effort is lost to history. But back in 2017, a redditor called Vadermeer unearthed a key trove of documents from this era, in a Goodwill Outlet store in Seattle:

https://www.reddit.com/r/VintageApple/comments/5vjsow/found_internal_apple_memos_about_copy_protection/

Vaderrmeer find was a Apple Computer binder from 1979, documenting the company's doomed "Software Security from Apple's Friends and Enemies" (SSAFE) project, an effort to make a copy-proof floppy:

https://archive.org/details/AppleSSAFEProject

The SSAFE files are an incredible read. They consist of Apple's best engineers beavering away for days, cooking up a new copy-proof floppy, which they would then hand over to Apple co-founder and legendary hardware wizard Steve Wozniak. Wozniak would then promptly destroy the copy-protection system, usually in a matter of minutes or hours. Wozniak, of course, got the seed capital for Apple by defeating AT&T's security measures, building a "blue box" that let its user make toll-free calls and peddling it around the dorms at Berkeley:

https://512pixels.net/2018/03/woz-blue-box/

Woz has stated that without blue boxes, there would never have been an Apple. Today, Apple leads the charge to restrict how you use your devices, confining you to using its official app store so it can skim a 30% vig off every dollar you spend, and corralling you into using its expensive repair depots, who love to declare your device dead and force you to buy a new one. Every pirate wants to be an admiral!

https://www.vice.com/en/article/tim-cook-to-investors-people-bought-fewer-new-iphones-because-they-repaired-their-old-ones/

Revisiting the early PC years for Picks and Shovels isn't just an excuse to bust out some PC nostalgiacore set-dressing. Picks and Shovels isn't just a face-paced crime thriller: it's a reflection on the enshittificatory impulses that were present at the birth of the modern tech industry.

But there is a nostalgic streak in Picks and Shovels, of course, represented by the other weird PC company in the tale. Computing Freedom is a scrappy PC startup founded by three women who came up as sales managers for Fidelity, before their pangs of conscience caused them to repent of their sins in luring their co-religionists into the Reverend Sirs' trap.

These women – an orthodox lesbian whose family disowned her, a nun who left her order after discovering the liberation theology movement, and a Mormon woman who has quit the church over its opposition to the Equal Rights Amendment – have set about the wozniackian project of reverse-engineering every piece of Fidelity hardware and software, to make compatible products that set Fidelity's caged victims free.

They're making floppies that work with Fidelity drives, and drives that work with Fidelity's floppies. Printers that work with Fidelity computers, and adapters so Fidelity printers will work with other PCs (as well as resprocketing kits to retrofit those printers for standard paper). They're making file converters that allow Fidelity owners to read their data in Visicalc or Lotus 1-2-3, and vice-versa.

In other words, they're engaged in "adversarial interoperability" – hacking their own fire-exits into the burning building that Fidelity has locked its customers inside of:

https://www.eff.org/deeplinks/2019/10/adversarial-interoperability

This was normal, back then! There were so many cool, interoperable products and services around then, from the Bell and Howell "Black Apple" clones:

https://forum.vcfed.org/index.php?threads%2Fbell-howell-apple-ii.64651%2F

to the amazing copy-protection cracking disks that traveled from hand to hand, so the people who shelled out for expensive software delivered on fragile floppies could make backups against the inevitable day that the disks stopped working:

https://en.wikipedia.org/wiki/Bit_nibbler

Those were wild times, when engineers pitted their wits against one another in the spirit of Steve Wozniack and SSAFE. That era came to a close – but not because someone finally figured out how to make data that you couldn't copy. Rather, it ended because an unholy coalition of entertainment and tech industry lobbyists convinced Congress to pass the Digital Millennium Copyright Act in 1998, which made it a felony to "bypass an access control":

https://www.eff.org/deeplinks/2016/07/section-1201-dmca-cannot-pass-constitutional-scrutiny

That's right: at the first hint of competition, the self-described libertarians who insisted that computers would make governments obsolete went running to the government, demanding a state-backed monopoly that would put their rivals in prison for daring to interfere with their business model. Plus ça change: today, their intellectual descendants are demanding that the US government bail out their "anti-state," "independent" cryptocurrency:

https://www.citationneeded.news/issue-78/

In truth, the politics of tech has always contained a faction of "anti-government" millionaires and billionaires who – more than anything – wanted to wield the power of the state, not abolish it. This was true in the mainframe days, when companies like IBM made billions on cushy defense contracts, and it's true today, when the self-described "Technoking" of Tesla has inserted himself into government in order to steer tens of billions' worth of no-bid contracts to his Beltway Bandit companies:

https://www.reuters.com/world/us/lawmakers-question-musk-influence-over-verizon-faa-contract-2025-02-28/

The American state has always had a cozy relationship with its tech sector, seeing it as a way to project American soft power into every corner of the globe. But Big Tech isn't the only – or the most important – US tech export. Far more important is the invisible web of IP laws that ban reverse-engineering, modding, independent repair, and other activities that defend American tech exports from competitors in its trading partners.

Countries that trade with the US were arm-twisted into enacting laws like the DMCA as a condition of free trade with the USA. These laws were wildly unpopular, and had to be crammed through other countries' legislatures:

https://pluralistic.net/2024/11/15/radical-extremists/#sex-pest

That's why Europeans who are appalled by Musk's Nazi salute have to confine their protests to being loudly angry at him, selling off their Teslas, and shining lights on Tesla factories:

https://www.malaymail.com/news/money/2025/01/24/heil-tesla-activists-protest-with-light-projection-on-germany-plant-after-musks-nazi-salute-video/164398

Musk is so attention-hungry that all this is as apt to please him as anger him. You know what would really hurt Musk? Jailbreaking every Tesla in Europe so that all its subscription features – which represent the highest-margin line-item on Tesla's balance-sheet – could be unlocked by any local mechanic for €25. That would really kick Musk in the dongle.

The only problem is that in 2001, the US Trade Rep got the EU to pass the EU Copyright Directive, whose Article 6 bans that kind of reverse-engineering. The European Parliament passed that law because doing so guaranteed tariff-free access for EU goods exported to US markets.

Enter Trump, promising a 25% tariff on European exports.

The EU could retaliate here by imposing tit-for-tat tariffs on US exports to the EU, which would make everything Europeans buy from America 25% more expensive. This is a very weird way to punish the USA.

On the other hand, not that Trump has announced that the terms of US free trade deals are optional (for the US, at least), there's no reason not to delete Article 6 of the EUCD, and all the other laws that prevent European companies from jailbreaking iPhones and making their own App Stores (minus Apple's 30% commission), as well as ad-blockers for Facebook and Instagram's apps (which would zero out EU revenue for Meta), and, of course, jailbreaking tools for Xboxes, Teslas, and every make and model of every American car, so European companies could offer service, parts, apps, and add-ons for them.

When Jeff Bezos launched Amazon, his war-cry was "your margin is my opportunity." US tech companies have built up insane margins based on the IP provisions required in the free trade treaties it signed with the rest of the world.

It's time to delete those IP provisions and throw open domestic competition that attacks the margins that created the fortunes of oligarchs who sat behind Trump on the inauguration dais. It's time to bring back the indomitable hacker spirit that the Bill Gateses of the world have been trying to extinguish since the days of the "open letter to hobbyists." The tech sector built a 10 foot high wall around its business, then the US government convinced the rest of the world to ban four-metre ladders. Lift the ban, unleash the ladders, free the world!

In the same way that futuristic sf is really about the present, Picks and Shovels, an sf novel set in the 1980s, is really about this moment.

I'm on tour with the book now – if you're reading this today (Mar 4) and you're in DC, come see me tonight with Matt Stoller at 6:30PM at the Cleveland Park Library:

https://www.loyaltybookstores.com/picksnshovels

And if you're in Richmond, VA, come down to Fountain Bookshop and catch me with Lee Vinsel tomorrow (Mar 5) at 7:30PM:

https://fountainbookstore.com/events/1795820250305

If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2025/03/04/object-permanence/#picks-and-shovels

[mariacallous]

Genetic testing company 23andMe, once a Silicon Valley darling valued at $6 billion, filed for Chapter 11 bankruptcy protection late Sunday as it prepares for a sale of the business. CEO Anne Wojcicki, who cofounded the company in 2006, has also stepped down after months of failed attempts to take the firm private.

As uncertainty about the company’s future reaches its peak, all eyes are on the trove of deeply personal—and potentially valuable—genetic data that 23andMe holds. Privacy advocates have long warned that the risk of entrusting genetic data to any institution is twofold—the organization could fail to protect it, but it could also hand over customer data to a new entity that they may not trust and didn’t choose.

California attorney general Rob Bonta reminded consumers in an alert on Friday that Californians have a legal right to ask that an organization delete their data. 23andMe customers in other states and countries largely do not have the same protections, though there is also a right to deletion for health data in Washington state’s My Health My Data Act and the European Union’s General Data Protection Regulation. Regardless of residency, all 23andMe customers should consider downloading anything they want to keep from the service and should then attempt to delete their information.

“This situation really brings home the point that there is still no national health privacy law in the US protecting your rights unless you live in California or Washington,” says Andrea Downing, an independent security researcher and cofounder of the patient-led digital rights nonprofit The Light Collective. “Meanwhile, we continue to evolve our understanding of how genetic information has value, but also has unique vulnerability.”

John Verdi, senior vice president of policy at the Future of Privacy Forum, says 23andMe’s new owner could revise the company’s privacy policies for new customers and new data collection, but the data it has already collected from current customers is subject to existing terms. “The company has legal obligations regarding information collected under the current policies,” he says.

Still, researchers emphasize that in practice, such a large transition will create real data exposure that is outside of 23andMe customers’ control. “In my opinion, these privacy policies—especially in the context of acquisitions in the venture capital and private equity space—aren't worth the paper they're printed on,” says longtime security researcher and data privacy advocate Kenn White. “For regular people out there who use these services, you're pretty much on your own. My advice is to request your data get deleted as soon as possible"

To delete your genetic data through 23andMe’s website, log in and then go to Settings in your profile. Scroll to 23andMe Data and then click View. At this point, you can choose to download a copy of your genetic information. Then scroll to Delete Data and click Permanently Delete Data. Once you initiate the process, you’ll receive an email from 23andMe to confirm. Click the link in the email to complete the deletion process. Additionally, you can direct 23andMe to destroy the biological sample it used to extract your DNA data if you previously authorized the company to keep it. Go to Settings and then Preferences.

You can also opt in to and out of participating in research at any time by updating your consent status in your account settings. If you opt out, 23andMe will stop using your information for research going forward and will discontinue use of your data within 30 days. This does not affect studies that have already been completed.

23andMe has never been profitable and has struggled to revamp its business model since it went public in 2021. Demand for its ancestry and health testing kits has been declining for years. And data privacy has had a role to play in the company’s dwindling fortunes after the company was hit with a major data breach in December 2023 that affected millions of customers. The incident led to a class action lawsuit, which 23andMe agreed to settle for $30 million.

Last summer, Wojcicki filed a proposal to take the company private, which was rejected by 23andMe’s board of directors. Shortly after, the company shuttered its in-house drug discovery unit, and its board members resigned en masse over Wojcicki’s strategic direction.

23andMe says it intends to continue operating as usual throughout the sale process and that there are no immediate changes to the way it stores, manages, or protects customer data. In an open letter to customers, the company said it will “seek to find a partner who shares our commitment to customer data privacy and allows our mission of helping people access, understand and benefit from the human genome to live on.” But the direction of 23andMe will ultimately be in the hands of whoever takes over the company.

“If there is a new owner that comes out of the bankruptcy process, that new owner steps into the shoes of 23andMe and takes over those assets,” says Jennifer Wagner, an assistant professor of law, policy, and engineering and anthropology at Penn State University.

“They would still be bound by the complex web of contractual agreements that are in place right now with users,” Wagner adds. “But I think it does give rise to some uncertainty in terms of whether or not a new player would have the same values or that same kind of culture that 23andMe was trying to cultivate.”

[allthebrazilianpolitics]

Threats to Democracy in Brazil: The Rise of Technofeudalism and the Assault on Democratic Institutions

We are living in a time when threats to democracy emerge from multiple fronts. Some of these threats are traditional—such as corruption and political violence—but others are novel and particularly insidious, leveraging digital technologies to undermine democratic institutions in unprecedented ways. One such force is what Cédric Durand coined as technofeudalism, a new order in which digital monopolies accumulate power, wealth, and control over political discourse, exacerbating social inequalities and manipulating public perception to their advantage.

At the turn of the 21st century, the rise of information technology brought great hope for decentralization, innovation, and democratization. The internet was hailed as a tool that would empower individuals, allowing them to access knowledge, connect across borders, and engage in civic participation. However, instead of delivering on these promises, the so-called “digital revolution” has created a landscape dominated by corporate monopolies, where a handful of platforms control the vast majority of information, economic transactions, and even social interactions.

This is the essence of technofeudalism: an economic system where control over data and digital infrastructure is concentrated in the hands of a few corporate actors—Google, Amazon, Meta, and Microsoft—who act as modern-day feudal lords. Unlike traditional market capitalism, where businesses compete for customers, these platforms do not simply participate in the economy; they own it. Users are not merely consumers but digital subjects who must pay rent—either through direct fees or by extracting their personal data—to access basic services.

In Brazil, this dynamic is particularly dangerous. As a country that has long struggled with economic inequality and institutional fragility, the rise of technofeudalism presents a severe challenge to sovereignty, democracy, and social justice. With digital platforms acting as arbiters of truth, political engagement, and economic opportunity, we must ask ourselves: Who controls Brazil’s democracy in the digital age? This question is motivated by five major threats.

Continue reading.

[tangentiallly]

Few described this opportunity as clearly as Google’s own chief economist, Hal Varian. Google’s data territory is by no means the only one that matters, but we mention Varian because, in a paper for a dry academic conference, he laid bare what we can now see as the exploitative inner logic of the data territory: how it enables corporations to use data to exclusively track and influence their customers. This territory (even the very idea of it) simply had not existed until two decades or so earlier.

Varian’s description started with something very simple: there was ‘now a computer in the middle of virtually every transaction’. A connected computer, of course, since a computer without an internet connection was of no use to Google. What followed were certain new social processes that Varian thought important:

Data extraction and analysis

Personalisation and customisation

Continuous experiments

New kinds of contracts due to better monitoring of what customers do

Data extraction is obvious: that’s the basic thing that, as we’ve seen, connected computers can do. Personalisation is also familiar: ad companies and social media platforms constantly tell us that by gathering more data about us, they can make their services more personally relevant to us.

But what about experiments? By ‘experiments’ Varian meant the possibility that platforms could use their control over computer-based transactions to systematically try out what pricing or other signals would be most effective. As to new contracts, Varian had spotted that, because every transaction conducted online was now directly observable, information streams that were before out of business’s reach suddenly became direct inputs to business. This changed the power relations between businesses and customers profoundly, because corporations could dictate interactions on their own terms (such as signing away some of your rights as an individual just by using a platform) and, in that way, secure your presence in their territory, a territory for continuous data extraction.

Put all this together, and you had a completely new space of commercial power right at the heart of everyday life. A new type of power relations had emerged based on the extraction of data.

Yet Varian was simply setting out the implications of the business model that his own company had long since pursued. Varian was one of those behind the design of Google’s system for auctioning ads, in real time, by drawing on the precise data Google possessed about a user’s likelihood to click on that specific ad (they had, after all, consistently been tracking what you searched for). Varian saw that every commercial transaction would over time come to operate on the basis of this new sort of tracking-based corporate power, that is, via exploiting data territory.

— Data Grab: The New Colonialism of Big Tech and How to Fight Back, by Ulises A. Mejias & Nick Couldry

[jackson-odoo-powerbi-expert]

Connect Odoo with Tableau Desktop

The Techfinna Odoo Tableau Connector is a integration tool that connects Odoo with Tableau, enabling real-time data extraction and visualization. With features like custom table selection, automatic schema detection, and support for live data refresh, it simplifies the process of creating dynamic dashboards and reports. This connector empowers businesses to unlock deeper insights and make data-driven decisions efficiently.

#odoo #odooerp #odoosoftware #odoomodule #crm #accounting #salesforce #connector #integration #odoo18 #odoo17 #microsoft #powerbi #desktop #odoo services#odooimplementation#google#odoo development company#odoo crm#microsoft#odoo erp#odoo#good omens

[digitaldetoxworld]

Machine Learning: A Comprehensive Overview

 Machine Learning (ML) is a subfield of synthetic intelligence (AI) that offers structures with the capacity to robotically examine and enhance from revel in without being explicitly programmed. Instead of using a fixed set of guidelines or commands, device studying algorithms perceive styles in facts and use the ones styles to make predictions or decisions. Over the beyond decade, ML has transformed how we have interaction with generation, touching nearly each aspect of our every day lives — from personalised recommendations on streaming services to actual-time fraud detection in banking.

Machine learning algorithms

What is Machine Learning?

At its center, gadget learning entails feeding facts right into a pc algorithm that allows the gadget to adjust its parameters and improve its overall performance on a project through the years. The more statistics the machine sees, the better it usually turns into. This is corresponding to how humans study — through trial, error, and revel in.

Arthur Samuel, a pioneer within the discipline, defined gadget gaining knowledge of in 1959 as “a discipline of take a look at that offers computers the capability to study without being explicitly programmed.” Today, ML is a critical technology powering a huge array of packages in enterprise, healthcare, science, and enjoyment.

Types of Machine Learning

Machine studying can be broadly categorised into 4 major categories:

1. Supervised Learning

 For example, in a spam electronic mail detection device, emails are classified as "spam" or "no longer unsolicited mail," and the algorithm learns to classify new emails for this reason.

Common algorithms include:

Linear Regression

Logistic Regression

Support Vector Machines (SVM)

Decision Trees

Random Forests

Neural Networks

2. Unsupervised Learning

Unsupervised mastering offers with unlabeled information. Clustering and association are commonplace obligations on this class.

Key strategies encompass:

K-Means Clustering

Hierarchical Clustering

Principal Component Analysis (PCA)

Autoencoders

three. Semi-Supervised Learning

It is specifically beneficial when acquiring categorised data is highly-priced or time-consuming, as in scientific diagnosis.

Four. Reinforcement Learning

Reinforcement mastering includes an agent that interacts with an surroundings and learns to make choices with the aid of receiving rewards or consequences. It is broadly utilized in areas like robotics, recreation gambling (e.G., AlphaGo), and independent vehicles.

Popular algorithms encompass:

Q-Learning

Deep Q-Networks (DQN)

Policy Gradient Methods

Key Components of Machine Learning Systems

1. Data

Data is the muse of any machine learning version. The pleasant and quantity of the facts directly effect the performance of the version. Preprocessing — consisting of cleansing, normalization, and transformation — is vital to make sure beneficial insights can be extracted.

2. Features

 Feature engineering, the technique of selecting and reworking variables to enhance model accuracy, is one of the most important steps within the ML workflow.

Three. Algorithms

Algorithms define the rules and mathematical fashions that help machines study from information. Choosing the proper set of rules relies upon at the trouble, the records, and the desired accuracy and interpretability.

4. Model Evaluation

Models are evaluated the use of numerous metrics along with accuracy, precision, consider, F1-score (for class), or RMSE and R² (for regression). Cross-validation enables check how nicely a model generalizes to unseen statistics.

Applications of Machine Learning

Machine getting to know is now deeply incorporated into severa domain names, together with:

1. Healthcare

ML is used for disorder prognosis, drug discovery, customized medicinal drug, and clinical imaging. Algorithms assist locate situations like cancer and diabetes from clinical facts and scans.

2. Finance

Fraud detection, algorithmic buying and selling, credit score scoring, and client segmentation are pushed with the aid of machine gaining knowledge of within the financial area.

3. Retail and E-commerce

Recommendation engines, stock management, dynamic pricing, and sentiment evaluation assist businesses boom sales and improve patron revel in.

Four. Transportation

Self-riding motors, traffic prediction, and route optimization all rely upon real-time gadget getting to know models.

6. Cybersecurity

Anomaly detection algorithms help in identifying suspicious activities and capacity cyber threats.

Challenges in Machine Learning

Despite its rapid development, machine mastering still faces numerous demanding situations:

1. Data Quality and Quantity

Accessing fantastic, categorised statistics is often a bottleneck. Incomplete, imbalanced, or biased datasets can cause misguided fashions.

2. Overfitting and Underfitting

Overfitting occurs when the model learns the education statistics too nicely and fails to generalize. 

Three. Interpretability

Many modern fashions, specifically deep neural networks, act as "black boxes," making it tough to recognize how predictions are made — a concern in excessive-stakes regions like healthcare and law.

4. Ethical and Fairness Issues

Algorithms can inadvertently study and enlarge biases gift inside the training facts. Ensuring equity, transparency, and duty in ML structures is a growing area of studies.

5. Security

Adversarial assaults — in which small changes to enter information can fool ML models — present critical dangers, especially in applications like facial reputation and autonomous riding.

Future of Machine Learning

The destiny of system studying is each interesting and complicated. Some promising instructions consist of:

1. Explainable AI (XAI)

Efforts are underway to make ML models greater obvious and understandable, allowing customers to believe and interpret decisions made through algorithms.

2. Automated Machine Learning (AutoML)

AutoML aims to automate the stop-to-cease manner of applying ML to real-world issues, making it extra reachable to non-professionals.

3. Federated Learning

This approach permits fashions to gain knowledge of across a couple of gadgets or servers with out sharing uncooked records, enhancing privateness and efficiency.

4. Edge ML

Deploying device mastering models on side devices like smartphones and IoT devices permits real-time processing with reduced latency and value.

Five. Integration with Other Technologies

ML will maintain to converge with fields like blockchain, quantum computing, and augmented fact, growing new opportunities and challenges.

[stuarttechnologybob]

How does data capture services benefit a business?

Data Capture services

In the current digital age, data secrecy is recognized as the most valuable asset for any business. However, collecting it manually and investing time in it personally is time-consuming and prone to errors, as it is subject to matters. That’s where data capture services come in. While these services enable the enterprises to collect, organize, store and process information quickly and accurately, resulting in more informed decisions and enhanced efficiency for the organization to go ahead.

Faster Access to Information:

Data-capturing services automate the process of gathering data from various sources, including documents, forms, emails, and other digital assets. As this process speeds up the process to access critical information, enabling employees to work more towards the betterment efficiently and respond promptly towards customer needs or business challenges.

Improved Accuracy and Reduced Errors:

Manual data entry and filling often leads and thrives towards mistakes as they can affect the ongoing business operations. With data capturing technology, information is extracted using tools such as OCR (Optical Character Recognition) and with the assistance of AI, ensuring a level of higher accuracy is maintained. At the same time, fewer errors means better outcomes and more reliable reports that have been generated.

Streamlined Business Operations:

By automating data collection, businesses can save time and resources. While the staff and operating users no longer have the need to spend hours by entering data by hand or their own, allowing them to have a keen look on more valuable tasks and selective concerns. This heads and drives toward enhanced productivity and smoother workflows and operations.

Enhanced Customer Service:

Quick and precise data collection assures that the customer records, queries, and transactions are handled efficiently and effectively with this technique adaption. This leads towards faster service delivery, fewer complaints, and a better overall customer experience—key factors in staying competitive.

Better Decision-Making:

Accurate and well-organized data gives leaders a clearer view of their business performance. With real-time insights from data capture, they can make informed and clear decisions by identifying the current trends, and respond to market changes with confidence with a complete detailed report.

Scalable for Growing Businesses:

As a business grows, managing large volumes of data becomes more difficult. Data capture services scale and grow with your company, handling increasing amounts and multiple sets of information without sacrificing the speed or accuracy. Many businesses trust experts like Suma Soft, IBM, Cyntexa, and Cignex for efficient data capture solutions. These providers offer tailored services that boost data accuracy, ensure fast turnaround, and support long-term digital transformation.

[normanstack]

Astraweb: The Home of Crypto Recovery in the Digital Age

In the ever-evolving world of cryptocurrency, security and access remain critical concerns. For every success story of early adopters turning modest investments into fortunes, there are unfortunate accounts of users losing access to their digital wallets due to forgotten passwords, phishing attacks, or compromised private keys. This is where Astraweb has carved out a vital niche — establishing itself as the go-to solution for crypto asset recovery.

The Need for Crypto Recovery

Cryptocurrency promises decentralized finance and ownership without intermediaries — but this power comes with a cost: total user responsibility. There is no central authority to call when access is lost. Millions of dollars in crypto assets are estimated to be trapped in inaccessible wallets. The stakes are high, and the traditional “write your password down and hope for the best” method has proven tragically inadequate.

Astraweb has stepped in to fill this gap, offering a technically advanced, ethically grounded, and user-focused recovery service for individuals and institutions alike.

Who is Astraweb?

Astraweb is a team of cybersecurity professionals, blockchain analysts, and ethical hackers dedicated to the recovery of lost digital assets. Known in online communities for their discretion and technical excellence, Astraweb has quietly built a reputation as the “home of crypto recovery” — a safe harbor in the sometimes stormy seas of decentralized finance.

Core Services Offered

Wallet Password Recovery  Utilizing a combination of brute force optimization, machine learning, and customized dictionary attacks, Astraweb helps users recover wallets with forgotten passwords. Their tools are especially effective with partially remembered credentials.

Seed Phrase Reconstruction  Lost or partial seed phrases are another major barrier to wallet access. Astraweb’s proprietary tools attempt to reconstruct valid mnemonic phrases based on user input and probabilistic modeling.

Phishing and Scam Mitigation  If your crypto assets have been stolen due to phishing attacks or scams, Astraweb provides investigation support and recovery options. While crypto transactions are irreversible, Astraweb works with partners and tracing tools like Chainalysis to help track and reclaim funds when possible.

Multi-Sig and Legacy Wallet Recovery  Many early wallets used now-defunct software or obscure security models. Astraweb specializes in navigating old formats, deprecated standards, and rare cryptographic setups.

Cold Wallet Restoration  Lost access to hardware wallets like Trezor, Ledger, or even encrypted USB drives? Astraweb can assist with forensic-level data recovery and hardware-based key extraction.

Why Astraweb Stands Out

Confidentiality First: Every case is handled with strict privacy. Your data and identity are protected at all stages of the recovery process.

Transparent Communication: Clients are updated at every step, with no vague promises or false guarantees.

No Recovery, No Fee: Astraweb operates on a results-based model. You only pay if your assets are successfully recovered.

Client Trust and Track Record

Though much of their work remains confidential due to the sensitive nature of crypto assets, Astraweb’s success stories span from everyday investors to high-net-worth individuals and even businesses affected by inaccessible wallets or theft.

Their community reputation and testimonials underscore one thing: they deliver.

Contact Astraweb

If you’ve lost access to your cryptocurrency wallet, or fallen victim to crypto fraud, don’t give up hope. Reach out to Astraweb for a professional assessment of your situation.

Email: Astraweb@cyberdude.com

Whether it’s one token or an entire portfolio, Astraweb may be your best shot at recovery.

[datapeakbyfactr]

AI’s Role in Business Process Automation

Automation has come a long way from simply replacing manual tasks with machines. With AI stepping into the scene, business process automation is no longer just about cutting costs or speeding up workflows—it’s about making smarter, more adaptive decisions that continuously evolve. AI isn't just doing what we tell it; it’s learning, predicting, and innovating in ways that redefine how businesses operate. 

From hyperautomation to AI-powered chatbots and intelligent document processing, the world of automation is rapidly expanding. But what does the future hold?

What is Business Process Automation? 

Business Process Automation (BPA) refers to the use of technology to streamline and automate repetitive, rule-based tasks within an organization. The goal is to improve efficiency, reduce errors, cut costs, and free up human workers for higher-value activities. BPA covers a wide range of functions, from automating simple data entry tasks to orchestrating complex workflows across multiple departments. 

Traditional BPA solutions rely on predefined rules and scripts to automate tasks such as invoicing, payroll processing, customer service inquiries, and supply chain management. However, as businesses deal with increasing amounts of data and more complex decision-making requirements, AI is playing an increasingly critical role in enhancing BPA capabilities. 

AI’s Role in Business Process Automation 

AI is revolutionizing business process automation by introducing cognitive capabilities that allow systems to learn, adapt, and make intelligent decisions. Unlike traditional automation, which follows a strict set of rules, AI-driven BPA leverages machine learning, natural language processing (NLP), and computer vision to understand patterns, process unstructured data, and provide predictive insights. 

Here are some of the key ways AI is enhancing BPA: 

Self-Learning Systems: AI-powered BPA can analyze past workflows and optimize them dynamically without human intervention. 

Advanced Data Processing: AI-driven tools can extract information from documents, emails, and customer interactions, enabling businesses to process data faster and more accurately. 

Predictive Analytics: AI helps businesses forecast trends, detect anomalies, and make proactive decisions based on real-time insights. 

Enhanced Customer Interactions: AI-powered chatbots and virtual assistants provide 24/7 support, improving customer service efficiency and satisfaction. 

Automation of Complex Workflows: AI enables the automation of multi-step, decision-heavy processes, such as fraud detection, regulatory compliance, and personalized marketing campaigns. 

As organizations seek more efficient ways to handle increasing data volumes and complex processes, AI-driven BPA is becoming a strategic priority. The ability of AI to analyze patterns, predict outcomes, and make intelligent decisions is transforming industries such as finance, healthcare, retail, and manufacturing. 

“At the leading edge of automation, AI transforms routine workflows into smart, adaptive systems that think ahead. It’s not about merely accelerating tasks—it’s about creating an evolving framework that continuously optimizes operations for future challenges.”

— Emma Reynolds, CTO of QuantumOps

Trends in AI-Driven Business Process Automation 

1. Hyperautomation 

Hyperautomation, a term coined by Gartner, refers to the combination of AI, robotic process automation (RPA), and other advanced technologies to automate as many business processes as possible. By leveraging AI-powered bots and predictive analytics, companies can automate end-to-end processes, reducing operational costs and improving decision-making. 

Hyperautomation enables organizations to move beyond simple task automation to more complex workflows, incorporating AI-driven insights to optimize efficiency continuously. This trend is expected to accelerate as businesses adopt AI-first strategies to stay competitive. 

2. AI-Powered Chatbots and Virtual Assistants 

Chatbots and virtual assistants are becoming increasingly sophisticated, enabling seamless interactions with customers and employees. AI-driven conversational interfaces are revolutionizing customer service, HR operations, and IT support by providing real-time assistance, answering queries, and resolving issues without human intervention. 

The integration of AI with natural language processing (NLP) and sentiment analysis allows chatbots to understand context, emotions, and intent, providing more personalized responses. Future advancements in AI will enhance their capabilities, making them more intuitive and capable of handling complex tasks. 

3. Process Mining and AI-Driven Insights 

Process mining leverages AI to analyze business workflows, identify bottlenecks, and suggest improvements. By collecting data from enterprise systems, AI can provide actionable insights into process inefficiencies, allowing companies to optimize operations dynamically. 

AI-powered process mining tools help businesses understand workflow deviations, uncover hidden inefficiencies, and implement data-driven solutions. This trend is expected to grow as organizations seek more visibility and control over their automated processes. 

4. AI and Predictive Analytics for Decision-Making 

AI-driven predictive analytics plays a crucial role in business process automation by forecasting trends, detecting anomalies, and making data-backed decisions. Companies are increasingly using AI to analyze customer behaviour, market trends, and operational risks, enabling them to make proactive decisions. 

For example, in supply chain management, AI can predict demand fluctuations, optimize inventory levels, and prevent disruptions. In finance, AI-powered fraud detection systems analyze transaction patterns in real-time to prevent fraudulent activities. The future of BPA will heavily rely on AI-driven predictive capabilities to drive smarter business decisions. 

5. AI-Enabled Document Processing and Intelligent OCR 

Document-heavy industries such as legal, healthcare, and banking are benefiting from AI-powered Optical Character Recognition (OCR) and document processing solutions. AI can extract, classify, and process unstructured data from invoices, contracts, and forms, reducing manual effort and improving accuracy. 

Intelligent document processing (IDP) combines AI, machine learning, and NLP to understand the context of documents, automate data entry, and integrate with existing enterprise systems. As AI models continue to improve, document processing automation will become more accurate and efficient. 

Going Beyond Automation

The future of AI-driven BPA will go beyond automation—it will redefine how businesses function at their core. Here are some key predictions for the next decade: 

Autonomous Decision-Making: AI systems will move beyond assisting human decisions to making autonomous decisions in areas such as finance, supply chain logistics, and healthcare management. 

AI-Driven Creativity: AI will not just automate processes but also assist in creative and strategic business decisions, helping companies design products, create marketing strategies, and personalize customer experiences. 

Human-AI Collaboration: AI will become an integral part of the workforce, working alongside employees as an intelligent assistant, boosting productivity and innovation. 

Decentralized AI Systems: AI will become more distributed, with businesses using edge AI and blockchain-based automation to improve security, efficiency, and transparency in operations. 

Industry-Specific AI Solutions: We will see more tailored AI automation solutions designed for specific industries, such as AI-driven legal research tools, medical diagnostics automation, and AI-powered financial advisory services. 

AI is no longer a futuristic concept—it’s here, and it’s already transforming the way businesses operate. What’s exciting is that we’re still just scratching the surface. As AI continues to evolve, businesses will find new ways to automate, innovate, and create efficiencies that we can’t yet fully imagine. 

But while AI is streamlining processes and making work more efficient, it’s also reshaping what it means to be human in the workplace. As automation takes over repetitive tasks, employees will have more opportunities to focus on creativity, strategy, and problem-solving. The future of AI in business process automation isn’t just about doing things faster—it’s about rethinking how we work all together.

Learn more about DataPeak:

[mostlysignssomeportents]

Enshittification isn’t caused by venture capital

Picks and Shovels is a new, standalone technothriller starring Marty Hench, my two-fisted, hard-fighting, tech-scam-busting forensic accountant. You can pre-order it on my latest Kickstarter, which features a brilliant audiobook read by Wil Wheaton.

Many of us have left the big social media platforms; far more of us wish we could leave them; and even those of us who've escaped from Facebook/Insta and Twitter still spend a lot of time trying to figure out how to get the people we care about off of them, too.

It's lazy and easy to think that our friends who are stuck on legacy platforms run by Zuckerberg and Musk lack the self-discipline to wean themselves off of these services, or lack the perspective to understand why it's so urgent to get away from them, or that their "hacked dopamine loops" have addicted them to the zuckermusk algorithms. But if you actually listen to the people who've stayed behind, you'll learn that the main reason our friends stay on legacy platforms is that they care about the other people there more than they hate Zuck or Musk.

They rely on them because they're in a rare-disease support group; or they all coordinate their kids' little league carpools there; or that's where they stay in touch with family and friends they left behind when they emigrated; or they're customers or the audience for creative labor.

All those people might want to leave, too, but it's really hard to agree on where to go, when to go, and how to re-establish your groups when you get somewhere else. Economists call this the "collective action problem." This problem creates "switching costs" – a lot of stuff you'll have to live without if you switch from legacy platforms to new ones. The collective action problem is hard to solve and the switching costs are very high:

https://pluralistic.net/2022/10/29/how-to-leave-dying-social-media-platforms/

That's why people stay behind – not because they lack perspective, or self-discipline, or because their dopamine loops have been hacked by evil techbro sorcerers who used Big Data to fashion history's first functional mind-control ray. They are locked in by real, material things.

Big Tech critics who attribute users' moral failings or platforms' technical prowess to the legacy platforms' "stickiness" are their own worst enemies. These critics have correctly identified that legacy platforms are a serious problem, but have totally failed to understand the nature of that problem or how to fix it. Thankfully, more and more critics are coming to understand that lock-in is the root of the problem, and that anti-lock-in measures like interoperability can address it.

But there's another major gap in the mainstream critique of social media. Critics of zuckermuskian media claim those services are so terrible because they're for-profit entities, capitalist enterprises hitched to the logic of extraction and profit above all else. The problem with this claim is that it doesn't explain the changes to these services. After all, the reason so many of us got on Twitter and Facebook and Instagram is because they used to be a lot of fun. They were useful. They were even great at times.

When tech critics fail to ask why good services turn bad, that failure is just as severe as the failure to ask why people stay when the services rot.

Now, the guy who ran Facebook when it was a great way to form communities and make friends and find old friends is the same guy who who has turned Facebook into a hellscape. There's very good reason to believe that Mark Zuckerberg was always a creep, and he took investment capital very early on, long before he started fucking up the service. So what gives? Did Zuck get a brain parasite that turned him evil? Did his investors get more demanding in their clamor for dividends?

If that's what you think, you need to show your working. Again, by all accounts, Zuck was a monster from day one. Zuck's investors – both the VCs who backed him early and the gigantic institutional funds whose portfolios are stuffed with Meta stock today – are not patient sorts with a reputation for going easy on entrepreneurs who leave money on the table. They've demanded every nickel since the start.

What changed? What caused Zuck to enshittify his service? And, even more importantly for those of us who care about the people locked into Facebook's walled gardens: what stopped him from enshittifying his services in the "good old days?"

At its root, enshittification is a theory about constraints. Companies pursue profit at all costs, but while you may be tempted to focus on the "at all costs" part of that formulation, you musn't neglect the "profits" part. Companies don't pursue unprofitable actions at all costs – they only pursue the plans that they judge are likely to yield profits.

When companies face real competitors, then some enshittificatory gambits are unprofitable, because they'll drive your users to competing platforms. That's why Zuckerberg bought Instagram: he had been turning the screws on Facebook users, and when Instagram came along, millions of those users decided that they hated Zuck more than they loved their friends and so they swallowed the switching costs and defected to Instagram. In an ill-advised middle-of-the-night memo to his CFO, Zuck defended spending $1b on Instagram on the grounds that it would recapture those Facebook escapees:

https://www.theverge.com/2020/7/29/21345723/facebook-instagram-documents-emails-mark-zuckerberg-kevin-systrom-hearing

A company that neutralizes, buys or destroys its competitors can treat its users far worse – invade their privacy, cheap out on moderation and anti-spam, etc – without losing their business. That's why Zuck's motto is "it is better to buy than to compete":

https://www.trtworld.com/magazine/zuckerberg-its-better-to-buy-than-compete-is-facebook-a-monopoly-42243

Of course, as a leftist, I know better than to count on markets as a reliable source of corporate discipline. Even more important than market discipline is government discipline, in the form of regulation. If Zuckerberg feared fines for privacy violations, or moderation failures, or illegal anticompetitive mergers, or fraudulent advertising systems that rip off publishers and advertisers, or other forms of fraud (like the "pivot to video"), he would treat his users better. But Facebook's rise to power took place during the second half of the neoliberal era, when the last shreds of regulatory muscle that survived the Reagan revolution were being devoured by GW Bush and Obama (and then Trump).

As cartels and monopolies took over our economy, most government regulators were neutered and captured. Public agencies were stripped of their powers or put in harness to attack small companies, customers, and suppliers who got in the way of monopolists' rent-extraction. That meant that as Facebook grew, Zuckerberg had less and less to fear from government enforcers who might punish him for enshittification where the markets failed to do so.

But it's worse than that, because Zuckerberg and other tech monopolists figured out how to harness "IP" law to get the government to shut down third-party technology that might help users resist enshittification. IP law is why you can't make a privacy-protecting ad-blocker for an app (and why companies are so desperate to get you to use their apps rather than the open web, and why apps are so dismally enshittified). IP law is why you can't make an alternative client that blocks algorithmic recommendations. IP law is why you can't leave Facebook for a new service and run a scraper that imports your waiting Facebook messages into a different inbox. IP law is why you can't scrape Facebook to catalog the paid political disinformation the company allows on the platform:

https://locusmag.com/2020/09/cory-doctorow-ip/

IP law's growth has coincided with Facebook's ascendancy – the bigger Facebook got, the more tempting it was to interoperators who might want to plug new code into it to protect Facebook users, and the more powers Facebook had to block even the most modest improvements to its service. That meant that Facebook could enshittify even more, without worrying that it would drive users to take unilateral, permanent action that would deprive it of revenue, like blocking ads. Once ad-blocking is illegal (as it is on apps), there's no reason not to make ads as obnoxious as you want.

Of course, many Facebook employees cared about their users, and for most of the 21st century, those workers were a key asset for Facebook. Tech workers were in short supply until just a couple years ago, when the platforms started round after round of brutal layoffs – 260,000 in 2023, another 150,000+ in 2024. Facebook workers may be furious about Zuckerberg killing content moderation, but he's not worried about them quitting – not with a half-million skilled tech workers out there, hunting for jobs. Fuck 'em. Let 'em quit:

https://www.404media.co/its-total-chaos-internally-at-meta-right-now-employees-protest-zuckerbergs-anti-lgbtq-changes/

This is what changed: the collapse of market, government, and labor constraints, and IP law's criminalization of disenshittifying, interoperable add-ons. This is why Zuck, an eternal creep, is now letting his creep flag fly so proudly today. Not because he's a worse person, but because he understands that he can hurt his users and workers to benefit his shareholders without facing any consequences. Zuckerberg 2025 isn't the most evil Zuck, he's the most unconstrained Zuck.

Same goes for Twitter. I mean, obviously, there's been a change in management at Twitter – the guy who's enshittifying it today isn't the guy who enshittified it prior to last year. Musk is speedrunning the enshittification curve, and yet Twitter isn't collapsing. Why not? Because Musk is insulated from consequences for fucking up – he's got a huge cushion of wealth, he's got advertisers who are desperate to reach his users, he's got users who can't afford to leave the service, he's got IP law that he can use to block interoperators who might make it easier to migrate to a better service. He was always a greedy, sadistic asshole. Now he's an unconstrained greedy, sadistic asshole. Musk 2025 isn't a worse person than Musk 2020. He's just more free to act on his evil impulses than he was in years gone by.

These are the two factors that make services terrible: captive users, and no constraints. If your users can't leave, and if you face no consequences for making them miserable (not solely their departure to a competitor, but also fines, criminal charges, worker revolts, and guerrilla warfare with interoperators), then you have the means, motive and opportunity to turn your service into a giant pile of shit.

That's why we got Jack Welch and his acolytes when we did. There were always evil fuckers just like them hanging around, but they didn't get to run GM until Ronald Reagan took away the constraints that would have punished them for turning GE into a giant pile of shit. Every economy is forever a-crawl with parasites and monsters like these, but they don't get to burrow into the system and colonize it until policymakers create rips they can pass through.

In other words, the profit motive itself is not sufficient to cause enshittification – not even when a for-profit firm has to answer to VCs who would shut down the company or fire its leadership in the face of unsatisfactory returns. For-profit companies chase profit. The enshittifying changes to Facebook and Twitter are cruel, but the cruelty isn't the point: the point is profits. If the fines – or criminal charges – Facebook faced for invading our privacy exceeded the ad-targeting revenue it makes by doing so, it would stop spying on us. Facebook wouldn't like it. Zuck would hate it. But he'd do it, because he spies on us to make money, not because he's a voyeur.

To stop enshittification, it is not necessary to eliminate the profit motive – it is only necessary to make enshittification unprofitable.

This is not to defend capitalism. I'm not saying there's a "real capitalism" that's good, and a "crony capitalism" or "monopoly capitalism" that's bad. All flavors of capitalism harm working people and seek to shift wealth and power from the public and democratic institutions to private interests. But that doesn't change the fact that there are, indeed, different flavors of capitalism, and they have different winners and losers. Capitalists who want to sell apps on the App Store or reach customers through Facebook are technofeudalism's losers, while Apple, Facebook, Google, and other Big Tech companies are technofeudalism's great winners.

Smart leftism pays attention to these differences, because they represent the potential fault lines in capitalism's coalition. These people all call themselves capitalists, they all give money and support to political movements that seek to crush worker power and human rights – but when the platforms win, the platforms' business customers lose. They are irreconcilably on different sides of a capitalism-v-capitalism fight that is every bit as important to them as the capitalism-v-socialism fight.

I'm saying that it's good praxis to understand these divisions in capitalism, because then we can exploit those differences to make real, material gains for human thriving and worker rights. Lumping all for-profit businesses together as identical and irredeemable is bad tactics.

Legacy social media is at a turning point. Two new systems built on open standards have emerged as a credible threat to the zuckermuskian model: Mastodon (built on Activitypub) and Bluesky (built on Atproto). The former is far more mature, with a huge network of federated servers run by all different kinds of institutions, from hobbyists to corporations, and it's overseen by a nonprofit. The latter has far more users, and is a VC-backed corporate entity, and while it is hypothetically federatable, there are no Bluesky services apart from the main one that you can leave for if Bluesky starts to enshittify.

That means that Bluesky has a ton of captive users, and has the lack of constraint that characterizes the enshittified legacy platforms it has tempted tens of millions of users away from. This is not a good place to be in, because it means that if the current management choose to enshittify Bluesky, they can, and it will be profitable. It also means that the company's VCs understand that they could replace the current management and replace them with willing enshittifiers and make more money.

This is why Bluesky is in a dangerous place: not because it is backed by VCs, not because it is a for-profit entity, but because it has captive users and no constraints. It's a great party in a sealed building with no fire exits:

https://pluralistic.net/2024/12/14/fire-exits/#graceful-failure-modes

Last week, I endorsed a project called Free Our Feeds, whose goals include hacking some fire exits into Bluesky by force majeure – that is, independently standing up an alternative Bluesky server that people can retreat to if Bluesky management changes, or has a change of heart:

https://pluralistic.net/2025/01/14/contesting-popularity/#everybody-samba

For some Mastodon users, Free Our Feeds is dead on arrival – why bother trying to make a for-profit project safer for its users when Mastodon is a perfectly good nonprofit alternative? Why waste millions developing a standalone Bluesky server rather than spending that money improving things in the Fediverse.

I believe strongly in improving the Fediverse, and I believe in adding the long-overdue federation to Bluesky. That's because my goal isn't the success of the Fediverse – it's the defeat of enshtitification. My answer to "why spend money fixing Bluesky?" is "why leave 20 million people at risk of enshittification when we could not only make them safe, but also create the toolchain to allow many, many organizations to operate a whole federation of Bluesky servers?" If you care about a better internet – and not just the Fediverse – then you should share this goal, too.

Many of the Fediverse's servers are operated by for-profit entities, after all. One of the Fediverse's largest servers (Threads) is owned by Meta. Threads users who feel the bite of Zuckerberg's decision to encourage homophobic, xenophobic and transphobic hate speech will find it easy to escape from Threads: they can set up on any Fediverse server that is federated with Threads and they'll be able to maintain their connections with everyone who stays behind.

The existence of for-profit servers in the Fediverse does not ruin the Fediverse (though I wouldn't personally use one of them). The fact that multiple neo-Nazi groups run their own Mastodon servers does not ruin the Fediverse (though I certainly won't use their servers). Not even the fact that Donald Trump's Truth Social is a Mastodon server does anything to ruin the Fediverse (not using that one, either).

This is the strength of federated, federatable social media – it disciplines enshittifiers by lowering switching costs, and if enshittifiers persist, it makes it easy for users to escape unshitted, because they don't have to solve the collective action problem. Any user can go to any server at any time and stay in touch with everyone else.

Mastodon was born free: free code, with free federation as a priority. Bluesky was not: it was born within a for-profit public benefit corporation whose charter offers some defenses against enshittification, but lacks the most decisive one: the federation that would let users escape should escape become necessary.

The fact that Mastodon was born free is quite unusual in the annals of the fight for a free internet. Most of the internet was born proprietary and had freedom foisted upon it. Unix was born within Bell Labs, property of the convicted monopolist AT&T. The GNU/Linux project set it free.

SMB was born proprietary within corporate walls of Microsoft, another corporate monopolist. SAMBA set it free.

The Office file formats were also born proprietary within Microsoft's walled garden: they were set free by hacker-activists who fought through a thick bureaucratic morass and Microsoft fuckery (including literally refusing to allow chairs to be set for advocates for Open Document Format) to give us formats that underlie everything from LibreOffice to Google Docs, Office365 to your web browser.

There is nothing unusual, in other words, about hacking freedom into something that is proprietary or just insufficiently free. That's totally normal. It's how we got almost everything great about computers.

Mastodon's progenitors should be praised for ensuring their creation was born free – but the fact that Bluesky isn't free enough is no reason to turn our back on it. Our response to anything that locks in the people we care about must be to shatter those locks, not abandon the people bound by the locks because they didn't heed to our warnings.

Audre Lorde is far smarter than me, but when she wrote that "the master's tools will never dismantle the master's house," she was wrong. There is no toolset better suited to conduct an orderly dismantling of a structure than the tools that built it. You can be sure it'll have all the right screwdriver bits, wrenches, hexkeys and sockets.

Bluesky is fine. It has features I significantly prefer to Mastodon's equivalent. Composable moderation is amazing, both a technical triumph and a triumph of human-centered design:

https://bsky.social/about/blog/4-13-2023-moderation

I hope Mastodon adopts those features. If someone starts a project to copy all of Bluesky's best features over to Mastodon, I'll put my name to the crowdfunding campaign in a second.

But Mastodon has one feature that Bluesky sorely lacks – the federation that imposes antienshittificatory discipline on companies and offers an enshittification fire-exit for users if the discipline fails. It's long past time that someone copied that feature over to Bluesky.

Check out my Kickstarter to pre-order copies of my next novel, Picks and Shovels!

If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2025/01/20/capitalist-unrealism/#praxis

[rise2research]

The Automation Revolution: How Embedded Analytics is Leading the Way

Embedded analytics tools have emerged as game-changers, seamlessly integrating data-driven insights into business applications and enabling automation across various industries. By providing real-time analytics within existing workflows, these tools empower organizations to make informed decisions without switching between multiple platforms.

The Role of Embedded Analytics in Automation

Embedded analytics refers to the integration of analytical capabilities directly into business applications, eliminating the need for separate business intelligence (BI) tools. This integration enhances automation by:

Reducing Manual Data Analysis: Automated dashboards and real-time reporting eliminate the need for manual data extraction and processing.

Improving Decision-Making: AI-powered analytics provide predictive insights, helping businesses anticipate trends and make proactive decisions.

Enhancing Operational Efficiency: Automated alerts and anomaly detection streamline workflow management, reducing bottlenecks and inefficiencies.

Increasing User Accessibility: Non-technical users can easily access and interpret data within familiar applications, enabling data-driven culture across organizations.

Industry-Wide Impact of Embedded Analytics

1. Manufacturing: Predictive Maintenance & Process Optimization

By analyzing real-time sensor data, predictive maintenance reduces downtime, enhances production efficiency, and minimizes repair costs.

2. Healthcare: Enhancing Patient Outcomes & Resource Management

Healthcare providers use embedded analytics to track patient records, optimize treatment plans, and manage hospital resources effectively.

3. Retail: Personalized Customer Experiences & Inventory Optimization

Retailers integrate embedded analytics into e-commerce platforms to analyze customer preferences, optimize pricing, and manage inventory.

4. Finance: Fraud Detection & Risk Management

Financial institutions use embedded analytics to detect fraudulent activities, assess credit risks, and automate compliance monitoring.

5. Logistics: Supply Chain Optimization & Route Planning

Supply chain managers use embedded analytics to track shipments, optimize delivery routes, and manage inventory levels.

6. Education: Student Performance Analysis & Learning Personalization

Educational institutions utilize embedded analytics to track student performance, identify learning gaps, and personalize educational experiences.

The Future of Embedded Analytics in Automation

As AI and machine learning continue to evolve, embedded analytics will play an even greater role in automation. Future advancements may include:

Self-Service BI: Empowering users with more intuitive, AI-driven analytics tools that require minimal technical expertise.

Hyperautomation: Combining embedded analytics with robotic process automation (RPA) for end-to-end business process automation.

Advanced Predictive & Prescriptive Analytics: Leveraging AI for more accurate forecasting and decision-making support.

Greater Integration with IoT & Edge Computing: Enhancing real-time analytics capabilities for industries reliant on IoT sensors and connected devices.

Conclusion

By integrating analytics within existing workflows, businesses can improve efficiency, reduce operational costs, and enhance customer experiences. As technology continues to advance, the synergy between embedded analytics and automation will drive innovation and reshape the future of various industries.

To know more: data collection and insights

data analytics services

[iotric1]

Transforming Businesses with IoT: How Iotric’s IoT App Development Services Drive Innovation

In these days’s fast-paced virtual world, companies should include smart technology to stay ahead. The Internet of Things (IoT) is revolutionizing industries by way of connecting gadgets, collecting actual-time data, and automating approaches for stronger efficiency. Iotric, a leading IoT app improvement carrier issuer, makes a speciality of developing contemporary answers that help businesses leverage IoT for boom and innovation.

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Enhance operational efficiency by automating methods Gain real-time insights with linked devices Reduce downtime thru predictive renovation Improve purchaser revel in with smart applications

Strengthen security with far off tracking

Iotric: A Leader in IoT App Development Iotric is a trusted name in IoT app development, imparting cease-to-stop solutions tailored to numerous industries. Whether you want an IoT mobile app, cloud integration, or custom firmware improvement, Iotric can provide modern answers that align with your commercial enterprise goals.

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Industries Benefiting from Iotric’s IoT Solutions Healthcare Iotric develops IoT-powered healthcare programs for far off patient tracking, clever wearables, and real-time health monitoring, making sure better patient care and early diagnosis.

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[cashfry]

Do you think Apple Products are overrated?

We all are very well aware of this fact that the security and the performance it offers is undeniably the best out of the best. Musicians, artist, film makers, businessman, students, everyone is crazy for it. Yet, Apple is criticized about the customer service like damage repair prices, sky touching prices of accessories, products at App Store, Storage limitations, Expandable Capacity, modifications or upgradability, battery, gaming experience.

So why is it yet overrated and people are going for this option. I was going through the internet and here is what I found out. I will summarize the whole thing in short,( in case if you plan to buy apple product, click here.)

So, The Ram Management is really impressive. Apple at 6gb or 8GB RAM, It beats any other 8GB Device variant whether it is Android or Windows. but in order to extract every ounce of the higher performance, it kills any background activity which sometime might lead to loss of unsaved data. Battery is really not at that level, charging time is still, I'd say not that better. Eco system is imressive.

And that is why artists prefer Apple products. Though it is very hard to upgrade Apple product and the price it costs is ridiculously high. Security is good, but so does limitation on supported games and apps.

However it is the best of the best productive product. And seamless connectivity with other Apple products makes the work of user easy, like it is so convenient that you will definitely love it. Camera is also competing against the DSLR's. So what is it that is left now.

But many people buy it just to show off. And the weightage of such buyers is much greater than deserving ones. Hence, it is now overrated. Because Linux is way way way better in resource management. Windows is much much better in upgradability, gaming and many other hardware beats Apple in benchmarks.

The cost is also another major factor that you can't really ignore. For servers Apple is really not preferred. Neither for competitive gaming.

We must know everything has their pros and cons. Apple is good. But it sometimes drives you crazy over little things. Like Lack of Storage, Closed Ecosystem, Limited upgradability and Software Compatibility.

It now totally depends up to you how you use it, what is your purpose. It is the user who decides whether it is worth it for him or not.

Thanks, That was my opinion, what's yours you can share with us. Also, I saw few leaked and rumored articles about Apple Fold Phones. Let's see what comes next. I am really excited to see what they offer this time.

If you are an Apple fan, here is something useful for you, : Airpods Exchange Offer Amazon