#automated texting service

[falkonsms]

Transforming Communication: How Text Messaging Services Are Revolutionizing Business, Events, and Healthcare

In a digital world where immediacy and personalization are critical, businesses and organizations are turning to text messaging to streamline communication and improve engagement. Whether it’s an automated texting service for appointment reminders or an event text messaging service for real-time event updates, SMS has become one of the most effective tools for reaching customers, clients, and stakeholders.

In this article, we’ll explore the power and versatility of business text messaging, including how it applies to healthcare texting, mass texting services, and even online texting platforms. Whether you’re a startup, a hospital, or a corporate brand, implementing smart SMS solutions can dramatically improve your communication strategy.

The Rise of Automated Texting Service Technology

An automated texting service allows businesses to schedule and send text messages automatically based on triggers, user behavior, or a set timeline. This hands-free approach improves efficiency while maintaining personalization.

Key benefits of an automated texting service include:

Appointment confirmations and reminders

Follow-ups after purchases or inquiries

Notifications for shipping, billing, and feedback requests

Customer onboarding and training workflows

Bulk Text Messaging: Reaching Thousands in Seconds

When it comes to time-sensitive messages, bulk text messaging is a powerful tool. It enables you to send a single message to hundreds or thousands of recipients simultaneously, making it ideal for announcements, promotions, or alerts.

Why businesses love bulk text messaging:

High open rates (over 95% within minutes)

Real-time reach for urgent updates

Customizable messaging for different segments

Seamless integration with CRMs and marketing tools

Organizations of all sizes — from schools to retailers — are leveraging bulk text messaging for everything from flash sales to emergency alerts, making it a go-to for high-impact communication.

Business Text App: Mobility Meets Professional Messaging

A business text app brings your SMS communications into the modern age. Designed for teams, it allows employees to send and manage text messages from desktops, tablets, or smartphones while keeping conversations organized and professional.

Features of a quality business text app:

Shared inbox with team collaboration tools

Auto-replies and keyword triggers

Integration with tools like Slack, Salesforce, and HubSpot

Secure messaging to protect client data

With a business text app, you can keep communication flowing smoothly, no matter where your team is working from. It also ensures compliance and audit trails, which are vital for regulated industries.

Business Text Messaging: Smarter Conversations at Scale

Business text messaging goes beyond one-way notifications. It supports two-way conversations that allow companies to build real relationships with customers, prospects, and employees.

Popular uses of business text messaging:

Customer support and live chat

Sales follow-ups and lead nurturing

Internal HR communications

Delivery and service updates

Unlike email or phone calls, business text messaging is unobtrusive and immediate — ideal for today’s always-on consumers. It’s also measurable, with open and response rates that significantly outperform traditional channels.

Choosing the Right Business Texting Software

Business texting software gives you a robust platform to manage SMS campaigns, automate workflows, and measure performance. It’s the engine behind powerful SMS strategies, helping businesses drive engagement and ROI.

Features to look for in business texting software:

Message templates and personalization tools

Automation and scheduling capabilities

Contact list segmentation

Compliance with TCPA and data privacy laws

Good business texting software allows for seamless coordination of mass messages, automated flows, and personalized interactions — making it an essential tool for modern marketing and operations.

Event Text Messaging: Better Engagement at Every Stage

Whether you’re organizing a conference, webinar, or fundraiser, event text messaging can boost attendance, reduce no-shows, and keep participants informed.

Ways to use event text messaging:

Send reminders leading up to the event

Share schedules, locations, and live updates

Promote speakers, sponsors, and sessions

Collect attendee feedback in real time

By planning and executing a strategic event text messaging plan, organizers can maximize impact and minimize confusion, especially for large-scale or multi-day events.

Event Text Messaging Service: End-to-End Event Support

An event text messaging service takes the pressure off event organizers by managing the entire SMS campaign — from setup to execution and reporting.

Benefits of an event text messaging service:

Customized campaign setup tailored to your event goals

Professional guidance on timing and message structure

24/7 support for live events and emergencies

Integrated analytics and attendee insights

Healthcare Texting: Secure, Compliant Communication

Healthcare texting has transformed how medical providers connect with patients. It enables clinics, hospitals, and dental offices to maintain timely, HIPAA-compliant communication while reducing phone traffic.

Examples of healthcare texting in action:

Appointment scheduling and reminders

Lab result notifications and prescription pick-up alerts

Post-op care instructions and surveys

Health awareness campaigns

For providers, healthcare texting improves operational efficiency and enhances patient satisfaction. For patients, it adds convenience and a sense of connection to their care providers.

Mass Texting Service: High-Impact Messaging at Scale

A mass texting service allows businesses and organizations to send messages to large groups with ease. It combines the simplicity of SMS with the power of segmentation, automation, and analytics.

Top use cases for a mass texting service:

Emergency notifications for schools and municipalities

Special offers for retail customers

Fundraising campaigns for nonprofits

Staff communications for enterprises

With a mass texting service, you can maintain consistent contact with your audience while optimizing your message delivery for timing, tone, and relevance.

Online Texting: Communication Without Boundaries

Online texting refers to the ability to send and receive SMS messages from any internet-connected device — no phone required. It’s ideal for remote teams, customer service agents, and businesses with global operations.

Advantages of online texting:

Access from web browsers or cloud-based apps

Easy integration with CRM and helpdesk software

Scalable for teams and campaigns

Enhanced record-keeping and tracking

Online texting ensures that your team stays connected with clients, patients, or prospects — anytime, anywhere, without needing to rely on personal devices.

Final Thoughts

In the age of instant communication, leveraging tools like an automated texting service, bulk text messaging, and business texting software is no longer optional — it’s essential. Whether you’re managing a medical practice, running events, or marketing a brand, smart SMS strategies can drive better engagement, stronger relationships, and faster growth.

From healthcare texting to mass texting services, and from event text messaging services to intuitive business text apps, the future of communication is fast, flexible, and mobile. Make sure your organization is ready to embrace it.

[teenagefeeling]

SCREAM my new car somehow automatically sent a text message on my behalf yesterday??????? i didn't even notice this until right now

[j-esbian]

incredible that the zillow app does not have a messages tab even though it has a messaging function

[traumadumpling]

Not my mom texting back the random conservative party campaign number that texted her 😂 shes telling them that there's no chance of her voting for "their frickin stupid party" 💀

[automatewheel]

https://automatewheel.com

[precallai]

Integrating AI Call Transcription into Your VoIP or CRM System

In today’s hyper-connected business environment, customer communication is one of the most valuable assets a company possesses. Every sales call, support ticket, or service request contains rich data that can improve business processes—if captured and analyzed properly. This is where AI call transcription becomes a game changer. By converting voice conversations into searchable, structured text, businesses can unlock powerful insights. The real value, however, comes when these capabilities are integrated directly into VoIP and CRM systems, streamlining operations and enhancing customer experiences.

Why AI Call Transcription Matters

AI call transcription leverages advanced technologies such as Automatic Speech Recognition (ASR) and Natural Language Processing (NLP) to convert real-time or recorded voice conversations into text. These transcripts can then be used for:

Compliance and auditing

Agent performance evaluation

Customer sentiment analysis

CRM data enrichment

Automated note-taking

Keyword tracking and lead scoring

Traditionally, analyzing calls was a manual and time-consuming task. AI makes this process scalable and real-time.

Key Components of AI Call Transcription Systems

Before diving into integration, it’s essential to understand the key components of an AI transcription pipeline:

Speech-to-Text Engine (ASR): Converts audio to raw text.

Speaker Diarization: Identifies and separates different speakers.

Timestamping: Tags text with time information for playback syncing.

Language Modeling: Uses NLP to enhance context, punctuation, and accuracy.

Post-processing Modules: Cleans up the transcript for readability.

APIs/SDKs: Interface for integration with external systems like CRMs or VoIP platforms.

Common Use Cases for VoIP + CRM + AI Transcription

The integration of AI transcription with VoIP and CRM platforms opens up a wide range of operational enhancements:

Sales teams: Automatically log conversations, extract deal-related data, and trigger follow-up tasks.

Customer support: Analyze tone, keywords, and escalation patterns for better agent training.

Compliance teams: Use searchable transcripts to verify adherence to legal and regulatory requirements.

Marketing teams: Mine conversation data for campaign insights, objections, and buying signals.

Step-by-Step: Integrating AI Call Transcription into VoIP Systems

Step 1: Capture the Audio Stream

Most modern VoIP systems like Twilio, RingCentral, Zoom Phone, or Aircall provide APIs or webhooks that allow you to:

Record calls in real time

Access audio streams post-call

Configure cloud storage for call files (MP3, WAV)

Ensure that you're adhering to legal and privacy regulations such as GDPR or HIPAA when capturing and storing call data.

Step 2: Choose an AI Transcription Provider

Several commercial and open-source options exist, including:

Google Speech-to-Text

AWS Transcribe

Microsoft Azure Speech

AssemblyAI

Deepgram

Whisper by OpenAI (open-source)

When selecting a provider, evaluate:

Language support

Real-time vs. batch processing capabilities

Accuracy in noisy environments

Speaker diarization support

API response latency

Security/compliance features

Step 3: Transcribe the Audio

Using the API of your chosen ASR provider, submit the call recording. Many platforms allow streaming input for real-time use cases, or you can upload an audio file for asynchronous transcription.

Here’s a basic flow using an API:

python

CopyEdit

import requests

response = requests.post(

    "https://api.transcriptionprovider.com/v1/transcribe",

    headers={"Authorization": "Bearer YOUR_API_KEY"},

    json={"audio_url": "https://storage.yourvoip.com/call123.wav"}

)

transcript = response.json()

The returned transcript typically includes speaker turns, timestamps, and a confidence score.

Step-by-Step: Integrating Transcription with CRM Systems

Once you’ve obtained the transcription, you can inject it into your CRM platform (e.g., Salesforce, HubSpot, Zoho, GoHighLevel) using their APIs.

Step 4: Map Transcripts to CRM Records

You’ll need to determine where and how transcripts should appear in your CRM:

Contact record timeline

Activity or task notes

Custom transcription field

Opportunity or deal notes

For example, in HubSpot:

python

CopyEdit

requests.post(

    "https://api.hubapi.com/engagements/v1/engagements",

    headers={"Authorization": "Bearer YOUR_HUBSPOT_TOKEN"},

    json={

        "engagement": {"active": True, "type": "NOTE"},

        "associations": {"contactIds": [contact_id]},

        "metadata": {"body": transcript_text}

    }

)

Step 5: Automate Trigger-Based Actions

You can automate workflows based on keywords or intent in the transcript, such as:

Create follow-up tasks if "schedule demo" is mentioned

Alert a manager if "cancel account" is detected

Move deal stage if certain intent phrases are spoken

This is where NLP tagging or intent classification models can add value.

Advanced Features and Enhancements

1. Sentiment Analysis

Apply sentiment models to gauge caller mood and flag negative experiences for review.

2. Custom Vocabulary

Teach the transcription engine brand-specific terms, product names, or industry jargon for better accuracy.

3. Voice Biometrics

Authenticate speakers based on voiceprints for added security.

4. Real-Time Transcription

Show live captions during calls or video meetings for accessibility and note-taking.

Challenges to Consider

Privacy & Consent: Ensure callers are aware that calls are recorded and transcribed.

Data Storage: Securely store transcripts, especially when handling sensitive data.

Accuracy Limitations: Background noise, accents, or low-quality audio can degrade results.

System Compatibility: Some CRMs may require custom middleware or third-party plugins for integration.

Tools That Make It Easy

Zapier/Integromat: For non-developers to connect transcription services with CRMs.

Webhooks: Trigger events based on call status or new transcriptions.

CRM Plugins: Some platforms offer native transcription integrations.

Final Thoughts

Integrating AI call transcription into your VoIP and CRM systems can significantly boost your team’s productivity, improve customer relationships, and offer new layers of business intelligence. As the technology matures and becomes more accessible, now is the right time to embrace it.

With the right strategy and tools in place, what used to be fleeting conversations can now become a core part of your data-driven decision-making process.

[notifymd-medicalansweringservice]

Discover how to ensure HIPAA compliance while texting dental patients with this comprehensive guide. Learn about HIPAA's privacy, security, and breach notification rules, understand who needs to comply, and explore the benefits of HIPAA-compliant texting. Avoid penalties and improve patient engagement by implementing secure communication practices. Looking to enhance your dental practice's communication while maintaining compliance? Consider notifyMD's dental answering services for secure, efficient patient outreach. Contact today to learn more and stay compliant!

[smsgatewayindia]

Simplify Your Communication for WhatsApp Business API Messages with SMSGatewayCenter's Shared Team Inbox (Live Agent Chat)

Businesses need to manage client relationships in an efficient and successful manner in the era of instant communication. With the help of the robust WhatsApp Business API, businesses can connect with their clients on a personal level. But handling these exchanges can get stressful, particularly for expanding companies that receive a lot of enquiries. This is where the Shared Team Inbox (Live Agent Chat) feature from SMSGatewayCenter is useful.

[srbachchan]

DAY 6274

Jalsa, Mumbai Aopr 20, 2025 Sun 11:17 pm

🪔 ,

April 21 .. birthday greetings and happiness to Ef Mousumi Biswas .. and Ef Arijit Bhattacharya from Kolkata .. 🙏🏽❤️🚩.. the wishes from the Ef family continue with warmth .. and love 🌺

The AI debate became the topic of discussion on the dining table ad there were many potent points raised - bith positive and a little indifferent ..

The young acknowledged it with reason and able argument .. some of the mid elders disagreed mildly .. and the end was kind of neutral ..

Blessed be they of the next GEN .. their minds are sorted out well in advance .. and why not .. we shall not be around till time in advance , but they and their progeny shall .. as has been the norm through generations ...

The IPL is now the greatest attraction throughout the day .. particularly on the Sunday, for the two on the day .. and there is never a debate on that ..

🤣

.. and I am most appreciative to read the comments from the Ef on the topic of the day - AI .. appreciative because some of the reactions and texts are valid and interesting to know .. the aspect expressed in all has a legitimate argument and that is most healthy ..

I am happy that we could all react to the Blog contents in the manner they have done .. my gratitude .. such a joy to get different views , valid and meaningful ..

And it is not the end of the day or the debate .. some impressions of the Gen X and some from the just passed Gen .. and some that were never ever the Gen are interesting as well :

The Printing Press (15th Century)

Fear: Scribes, monks, and elites thought it would destroy the value of knowledge, lead to mass misinformation, and eliminate jobs. Reality: It democratized knowledge, spurred the Renaissance and Reformation, and created entirely new industries—publishing, journalism, and education.

⸻

Industrial Revolution (18th–19th Century)

Fear: Machines would replace all human labor. The Luddites famously destroyed machinery in protest. Reality: Some manual labor jobs were displaced, but the economy exploded with new roles in manufacturing, logistics, engineering, and management. Overall employment and productivity soared.

⸻

Automobiles (Early 20th Century)

Fear: People feared job losses for carriage makers, stable hands, and horseshoe smiths. Cities worried about traffic, accidents, and social decay. Reality: The car industry became one of the largest employers in the world. It reshaped economies, enabled suburbia, and created new sectors like travel, road infrastructure, and auto repair.

⸻

Personal Computers (1980s)

Fear: Office workers would be replaced by machines; people worried about becoming obsolete. Reality: Computers made work faster and created entire industries: IT, software development, cybersecurity, and tech support. It transformed how we live and work.

⸻

The Internet (1990s)

Fear: It would destroy jobs in retail, publishing, and communication. Some thought it would unravel social order. Reality: E-commerce, digital marketing, remote work, and the creator economy now thrive. It connected the world and opened new opportunities.

⸻

ATMs (1970s–80s)

Fear: Bank tellers would lose their jobs en masse. Reality: ATMs handled routine tasks, but banks actually hired more tellers for customer service roles as they opened more branches thanks to reduced transaction costs.

⸻

Robotics & Automation (Factory work, 20th century–today)

Fear: Mass unemployment in factories. Reality: While some jobs shifted or ended, others evolved—robot maintenance, programming, design. Productivity gains created new jobs elsewhere.

The fear is not for losing jobs. It is the compromise of intellectual property and use without compensation. This case is slightly different.

I think AI will only make humans smarter. If we use it to our advantage.

That’s been happening for the last 10 years anyway

Not something new

You can’t control that in this day and age

YouTube & User-Generated Content (mid-2000s onward)

Initial Fear: When YouTube exploded, many in the entertainment industry panicked. The fear was that copyrighted material—music, TV clips, movies—would be shared freely without compensation. Creators and rights holders worried their content would be pirated, devalued, and that they’d lose control over distribution.

What Actually Happened: YouTube evolved to protect IP and monetize it through systems like Content ID, which allows rights holders to:

Automatically detect when their content is used

Choose to block, track, or monetize that usage

Earn revenue from ads run on videos using their IP (even when others post it)

Instead of wiping out creators or studios, it became a massive revenue stream—especially for musicians, media companies, and creators. Entire business models emerged around fair use, remixes, and reactions—with compensation built in.

Key Shift: The system went from “piracy risk” to “profit partner,” by embracing tech that recognized and enforced IP rights at scale.

This lead to higher profits and more money for owners and content btw

You just have to restructure the compensation laws and rewrite contracts

It’s only going to benefit artists in the long run ‎

Yes

They can IP it

That is the hope

It’s the spread of your content and material without you putting a penny towards it

Cannot blindly sign off everything in contracts anymore. Has to be a lot more specific.

Yes that’s for sure

“Automation hasn’t erased jobs—it’s changed where human effort goes.”

Another good one is “hard work beats talent when talent stops working hard”

Which has absolutely nothing to with AI right now but 🤣

These ladies and Gentlemen of the Ef jury are various conversational opinions on AI .. I am merely pasting them for a view and an opinion ..

And among all the brouhaha about AI .. we simply forgot the Sunday well wishers .. and so ..

my love and the length be of immense .. pardon

Amitabh Bachchan

[cafterdark]

You always struggled with doing tasks. Between the procrastination, executive dysfunction, and exhaustion, even cleaning the dishes was a herculean task. It got so bad that it started to affect your work, leading to a stern talk from your boss. That's why, when your friend Jess, told you about her job's, Auton Industries, new productivity improvement services, you were willing to give it a shot.

The tech itself was simple, just a pair of dark sunglasses, indistinguishable from any normal pair. When you put it on, it prompted you with the text "Unit 4372 Settings" and hundreds of sliders and buttons. It overwhelmed you, so you picked the default options. A nice ding played and the actual software began.

On the right side of your vision, a list of task crept down, tasks and subtasks ranging from "Clean Dishes (32)" to "Improve Health (15)." The glasses highlighted various objects, with commands like "Clean", "Move", "Throw Away." Every time you completed a task, the highlight went green and dissipated, a speaker whispering sweet encouragement into your ear, followed by the same soft ding.

Put away some loose papers.

"Good Job!" Ding!

Finally take out the trash

"Great Work!" Ding!

Vacuum the floors.

"Keep Going!" Ding!

Every time you completed a task, that little bit of encouragement, that pleasurable ding, sank into your chest, making you feel warm, even more, appreciated. It was a feeling no other job or hobby had ever given you. When you were done with all your tasks, the shower of praise and dings you got was intoxicating.

You didn't admit it, but it was addictive. Soon, you began chasing the high of completing tasks, a depression following after finishing. You felt so useful following its commands, so appreciated when reviving its praise. You started helping friends clean their houses, just to get more. When you cleaned Jess's house, she had this grin that said she knew, as impossible as that was. Something fluttered in your stomach as she observed your work, giving her own compliments on top of the glasses. By the end, you could hardly stand with how much appreciation you received.

After, a new notification popped up on your glasses as you put them on in the morning.

"Due to your overwhelming success with our program, Auton Industries extends the offer to join our Advance Productivity program."

Needless to say, you joined immediately, and after many, many lengthy terms of service signed, a new piece of tech was sent to your home.

It was a full face mask, the face impenetrable black glass that reflected yourself. The instructions were simple. You put the mask on before you went to bed, and took it off in the morning. While you slept, the mask would play subliminal messages that increased the effectiveness of the productivity training.

You expected strange dreams from it, but all that greeted you was some beeps and soft static. In the morning, you felt better rested than ever before. Your exhaustion was gone.

The effects were immediate. Each completed task's made you feel so appreciated, each compliment and ding rocking through your body. On top of the mask, the glasses had gotten an update, with a whole new host of compliments.

Get dressed for work

"Good girl!" Ding!

Clean morning dishes

"Good Unit!" Ding!

Any discomfort with the wording was washed away by the appreciation you felt. It was complimenting you! You were useful! That couldn't be bad. By the time you were done, you needed to change underwear, and any thought of taking them off for work was excised from your mind.

The rest of the update showed itself as you began your job. Tasks had been made specifically for your work, and even what to say on calls, something you always struggled with, was automated. You found it so easy to sink into a pleasurable trance, following what the glasses told you to, shaking with every compliment. By the end of the shift, you had gotten more work done that ever before, and even got appreciation from the boss.

This process of wearing the mask while you slept, glasses while you were awake continued. And despite a few occasions like accidentally almost wearing the mask to work, things were going great, it... you were feeling so appreciated. Jess checked in on you more, keeping track of your progress. She seemed overwhelming happy with the results, calling you one of their best units. Something about the way she said that made it you shiver.

Then one day, a new package arrived at the door. You didn't remember ordering it, but then again, you didn't remember a lot of stuff now days. You fell into a loving haze of appreciation and usefulness and let the programing command it you.

A new task popped up, top of the list, most important:

"Open Package"

You followed without question.

"Good Girl!" Ding!

Inside was a latex suit.

"Put On Uniform"

The suit slipped on like a glove, each part lovingly crafted for your body. Somewhere in the back of your mind, you noticed it was a lot curvier than you, a lot more feminine, but it was soon buried by:

"Good Unit!" Ding!

"Put On Headset"

"Good Unit!" Ding!

Silly you, you already had it on!

"Repeat"

"It is a good drone"

"It is a good drone," You said

Ding!

"It is a Useful drone."

"It is a useful drone."

Ding!

"It is an Appreciated Drone"

"It is an Appreciated Drone," it said.

Ding!

It shuttered

"Calibration Complete, State Designation."

"Unit 4372"

"Good Drone" Ding!

If it still had control of its body, its knees would've buckled.

"Assume Transportation Position"

It fell to its knees, arms crossing behind its back and locking.

"Wait for Unit's owner to arrive, repeat mantra."

"It is a good drone, it is an useful drone, it is an appreciated drone, it is a good drone..."

... ... ...

"So there she is."

"Owner Arrival Acknowledged, cease previous instructions."

Unit 4372 looked to the voice, and saw its owner. Something in the back of its systems screamed recognition, attempting to hijack its programing to give Owner a name. Something that started with a J, but a simple touch by Owner drowned it all away.

"My star unit," Owner said. "Look how you've turned out."

Unit 4372 squirmed. It was so appreciated, so useful

"Come on, let's get you home."

If it could, Unit 4372 would've smiled.

[p1nkprincess444]

MOTEL SIX - TOM KAULITZ

female!reader x tom kaulitz

word count: 1,184

contents: 18+, cheating, mentions of drugs and alcohol, angst

 It was dark as you stumbled up the stairs clinging to the arm of your “boyfriend”. His hands were wandering more than usual but you were too drunk to pay it any mind. You both stumbled into the room taking only a few before collapsing onto the bed with him. Your brow furrowed when your “boyfriend's” lips connected with your neck. You felt the rough chapped skin against your neck, but you always remembered them as soft and gentle. You pushed the thoughts aside believing it to just be the alcohol clouding your senses. 

Tom slowly made his ascent up the staircase still nursing a beer. His words were slurring as he called out for you. He began pushing open doors that line the upstairs halls. He slowly stumbled to the last door calling out your name until the sight in front of him immediately made him sober up. Tom’s eyes locked onto you as you laid underneath a stranger he’s never seen before. Your clothes laid strewn around the room, your legs locked around the boy as his hips slammed into yours. Tom was left shocked in the doorway, the girl he loved was cheating on him so blatantly, how could she do this to him? 

Tom’s hand locked around the back of the boy’s neck as he yanked him off you. Confusion filled your mind as you stared at Tom who was standing in front of you, how was he fully clothes when he was just fucking you? Your brow furrowed as you stared up at an agitated looking Tom. Before you could even explain yourself he was walking out the door. You chased after him calling out his name desperate to grab his attention.

“ Tom- please jus’ wait! ”

He watched as you could barely keep your balance while you chased him out to his car, “ Just- stop you’re a fuckin’ mess. ”

“ I thought he was you. I- didn’t know! ” All my words were slurring together as I desperately tried to explain as Tom climbed into his car.

“ How were you so fucking drunk you couldn’t tell the difference between me and some random guy?! I’m done with you, can’t even fucking look at you. ” Tom’s expression was one of disgust as he slammed the car door in your face. 

You pounded on the car door screaming at Tom as he drove off leaving you there. You dropped down and sat on the curb as you sobbed into your hands.

 It felt like hours you were sat sobbing on the sidewalk until someone’s hand gently grabbed your shoulder. It was one of Tom’s friends who had come to the party with you. 

“ Come on, you can’t stay here all night. ” You followed him as he gently sat you in the passenger side of his car. The soft hum of the engine filled the silent car as Georg drove. 

He didn’t bother to take you back to your apartment you shared with Tom, instead he brought you to the closest motel. 

Days turned into weeks as your calls and texts to Tom went unanswered. You didn’t have the guts to return the apartment you once shared together, as you remained alone in the motel room. The days began to fade together as you spent your nights partying desperate to either see Tom by chance or just forget him in general. Weeks seemingly turned into months and your appearance reflected your turmoil. Your hair was growing matted and tangled along with your figure growing thinner. Dark bags showed under your eyes as once again you dialed Tom’s number on your cell.

“ This number is no longer in service. ”

Tears pricked your eyes as you tried again but you were met with the same results. 

It wasn’t until you managed to borrow someone’s phone at a party that you were able to try Tom’s number again. This time instead of a cold robotic automated message greeting you it was his voice. He sounded tired and groggy as he asked who it was. 

“ Tom, please don’t hang up. ” 

A chill ran down Tom’s spine when he heard your voice. He didn’t answer as he tried to figure out if he was dreaming or not. 

“ P- Please just come see me, mm’ at a motel on sixth. Room 108 please, just come tomorrow. ”

With no answer Tom hung up the phone. You could feel the tears pricking your eyes as you handed the phone back to its owner. 

You stayed at the motel all day constantly checking your phone for the time as you waited for Tom to show up. It was nearing 10 pm before a firm knocking resounded through the motel room. When you opened the door Tom was dressed in soft grey sweatpants along with one of his classic oversized t-shirts.

“ Can I come in? ”

You quickly nodded before moving aside from the doorway letting Tom enter. His eyes scanned the dingy motel room that was littered with drug paraphernalia and empty bottles of alcohol. He turned back to face you taking in your horribly disheveled appearance. He had never seen you this broken before in the time he’s known you. 

 “ How long have you been staying here? ”

“ Since the party- Georg brought me. ”

Tom nodded before taking a seat on the bed. You hesitantly joined Tom on the bed making it squeak under the combined weight of your bodies.

“ I miss you at home with me. ” Tom sounded weak and defeated as his hand slowly moved to grasp yours. 

No words were exchanged before Tom’s lips were pressed against yours. Your head was spinning as his hands moved under your clothes. His lips only left yours for a moment to yank your shirt over your head before his followed. Tom wasn’t gentle about anything as he finished stripping your clothes off. Your clothes laid in a small pile on the floor as Tom pushed open your legs. His nails dug into the plush skin of your thighs before his cock slammed into you. You couldn’t hold back the loud moans that fell from your lips. One of Tom’s hands abandoned its place on your thighs moving up to push the hair from your face before gripping your jaw forcing you to look at him. 

“ Du gehörst mir, nur mir. ” { You’re mine, only mine.}

You could only nod before more cries of pleasure spewed from your lips. 

“ Ich werde den nächsten Mann töten, der dich berührt. ” { I’ll kill the next man who touches you.}

Tom’s voice grew huskier with each movement of his hips. His thrusts grew needier as he tried to hold back his impending release. He watched as you writhed in pleasure underneath him, watching as your eyes rolled back in your head followed soon by your back arching and your cunt squeezing him tight as you came. Tom didn’t bother to pull out as he let his cum shoot deep inside your cunt. 

You both laid breathless and sweaty together tangled up in the sheets that covered the motel bed. 

“ Du wirst mich nie wieder verlassen. ” {You're never leaving me again.}

[kimpossibooty]

Gnome tidings to you all

The time has come! NeurotiCity texts are being upgraded to a subscription system!

There are a couple of reasons for this, but largely it comes down to the scale of the project. This has blown up well past what I ever anticipated, and it's getting harder to manage it all manually. This will help me invest in actually automating the texts in a way that enhances how the service actually acts, and it helps make the time I spend on this justifiable so I'm not doing crazy amounts of labor for a relatively small amount (which I've been doing up to this point). I'm having a ton of fun, and it's a passion project, but I'm putting hours of work in each day and a one-time small fee just can't justify that anymore.

So, to compensate for the change in setup, I'm expanding my services! In addition to Gnome Facts, I will now also be offering options for Wizards, Frogs, Ghosts, and Centaurs!

I'm also offering emails for a lower cost, since they're easier to automate, and I have a Telegram set up for international pranks at no extra cost!

Both my clients and targets are having a GREAT time with this, and I'd love to bring that happiness to more people, so come join in the fun! Here's feedback that the recipients of these facts have given so far!

You can even sign yourself up for daily doses of delight! Please let me know if you have any questions, or message me to talk about signing multiple people up!

Come join us on Patreon for more classic hijinks! And remember, there's no place like gnome!

also every member helps a disabled bisexual pay down heavy debts that stacked up out of nowhere so. like. solidarity.

[collapsedsquid]

I have a personal Gmail account which I use for correspondence about a book project I am working on. I woke up one morning in November to discover that I could no longer access it. A message from Google said my access had been “restricted globally” because “it looks as though Gmail has been used to send unwanted content. Spamming is a violation of Google’s policies.” The note said the decision had been made by “automatic processing” and that if I thought it was a mistake, I could submit an appeal. I had not sent any spam and couldn’t imagine why Google’s algorithm thought that I had. That made it hard to know what to write in the “appeal” text box, other than a panicked version of something like, “I didn’t do it (whatever it is)!” and, “Please help, I really need access to my email and my files”. (To my relief, I realised later that I hadn’t lost access to my drive.) Two days later, I heard back: “After reviewing your appeal, your account’s access remains restricted for this service.” I wasn’t given any more information on what I had supposedly done or why the appeal had been rejected, but was told that “if you disagree with this decision, you can submit another appeal.” I tried again and was rejected again. I did this a few more times — curious, at this point, about how long this doom loop could continue. A glance at Reddit suggested other people had been through similar things. Eventually, I gave up. (Google declined to comment on the record.) Among regulators, one popular answer to the question of how to make automated decisions more “fair” is to insist that people can request a human to review them. But how effective is this remedy? For one thing, humans are prone to “automation complacency” — a tendency to trust the machine too much. In the case of the UK’s Post Office scandal, for example, where sub-postmasters were wrongly accused of theft because of a faulty computer system called Horizon, a judge in 2019 concluded that people at the Post Office displayed “​​a simple institutional obstinacy or refusal to consider any possible alternatives to their view of Horizon”. [...] As for my email account, when I decided to write about my experience for this column, I emailed Google’s press office with the details to see if I could discuss the issue. By the end of the day, my access to my email account had been restored. I was pleased, of course, but I don’t think many people would see that as particularly fair either.

Unfriendly AI

[precallai]

How AI Is Revolutionizing Contact Centers in 2025

As contact centers evolve from reactive customer service hubs to proactive experience engines, artificial intelligence (AI) has emerged as the cornerstone of this transformation. In 2025, modern contact center architectures are being redefined through AI-based technologies that streamline operations, enhance customer satisfaction, and drive measurable business outcomes.

This article takes a technical deep dive into the AI-powered components transforming contact centers—from natural language models and intelligent routing to real-time analytics and automation frameworks.

1. AI Architecture in Modern Contact Centers

At the core of today’s AI-based contact centers is a modular, cloud-native architecture. This typically consists of:

NLP and ASR engines (e.g., Google Dialogflow, AWS Lex, OpenAI Whisper)

Real-time data pipelines for event streaming (e.g., Apache Kafka, Amazon Kinesis)

Machine Learning Models for intent classification, sentiment analysis, and next-best-action

RPA (Robotic Process Automation) for back-office task automation

CDP/CRM Integration to access customer profiles and journey data

Omnichannel orchestration layer that ensures consistent CX across chat, voice, email, and social

These components are containerized (via Kubernetes) and deployed via CI/CD pipelines, enabling rapid iteration and scalability.

2. Conversational AI and Natural Language Understanding

The most visible face of AI in contact centers is the conversational interface—delivered via AI-powered voice bots and chatbots.

Key Technologies:

Automatic Speech Recognition (ASR): Converts spoken input to text in real time. Example: OpenAI Whisper, Deepgram, Google Cloud Speech-to-Text.

Natural Language Understanding (NLU): Determines intent and entities from user input. Typically fine-tuned BERT or LLaMA models power these layers.

Dialog Management: Manages context-aware conversations using finite state machines or transformer-based dialog engines.

Natural Language Generation (NLG): Generates dynamic responses based on context. GPT-based models (e.g., GPT-4) are increasingly embedded for open-ended interactions.

Architecture Snapshot:

plaintext

CopyEdit

Customer Input (Voice/Text)

       ↓

ASR Engine (if voice)

       ↓

NLU Engine → Intent Classification + Entity Recognition

       ↓

Dialog Manager → Context State

       ↓

NLG Engine → Response Generation

       ↓

Omnichannel Delivery Layer

These AI systems are often deployed on low-latency, edge-compute infrastructure to minimize delay and improve UX.

3. AI-Augmented Agent Assist

AI doesn’t only serve customers—it empowers human agents as well.

Features:

Real-Time Transcription: Streaming STT pipelines provide transcripts as the customer speaks.

Sentiment Analysis: Transformers and CNNs trained on customer service data flag negative sentiment or stress cues.

Contextual Suggestions: Based on historical data, ML models suggest actions or FAQ snippets.

Auto-Summarization: Post-call summaries are generated using abstractive summarization models (e.g., PEGASUS, BART).

Technical Workflow:

Voice input transcribed → parsed by NLP engine

Real-time context is compared with knowledge base (vector similarity via FAISS or Pinecone)

Agent UI receives predictive suggestions via API push

4. Intelligent Call Routing and Queuing

AI-based routing uses predictive analytics and reinforcement learning (RL) to dynamically assign incoming interactions.

Routing Criteria:

Customer intent + sentiment

Agent skill level and availability

Predicted handle time (via regression models)

Customer lifetime value (CLV)

Model Stack:

Intent Detection: Multi-label classifiers (e.g., fine-tuned RoBERTa)

Queue Prediction: Time-series forecasting (e.g., Prophet, LSTM)

RL-based Routing: Models trained via Q-learning or Proximal Policy Optimization (PPO) to optimize wait time vs. resolution rate

5. Knowledge Mining and Retrieval-Augmented Generation (RAG)

Large contact centers manage thousands of documents, SOPs, and product manuals. AI facilitates rapid knowledge access through:

Vector Embedding of documents (e.g., using OpenAI, Cohere, or Hugging Face models)

Retrieval-Augmented Generation (RAG): Combines dense retrieval with LLMs for grounded responses

Semantic Search: Replaces keyword-based search with intent-aware queries

This enables agents and bots to answer complex questions with dynamic, accurate information.

6. Customer Journey Analytics and Predictive Modeling

AI enables real-time customer journey mapping and predictive support.

Key ML Models:

Churn Prediction: Gradient Boosted Trees (XGBoost, LightGBM)

Propensity Modeling: Logistic regression and deep neural networks to predict upsell potential

Anomaly Detection: Autoencoders flag unusual user behavior or possible fraud

Streaming Frameworks:

Apache Kafka / Flink / Spark Streaming for ingesting and processing customer signals (page views, clicks, call events) in real time

These insights are visualized through BI dashboards or fed back into orchestration engines to trigger proactive interventions.

7. Automation & RPA Integration

Routine post-call processes like updating CRMs, issuing refunds, or sending emails are handled via AI + RPA integration.

Tools:

UiPath, Automation Anywhere, Microsoft Power Automate

Workflows triggered via APIs or event listeners (e.g., on call disposition)

AI models can determine intent, then trigger the appropriate bot to complete the action in backend systems (ERP, CRM, databases)

8. Security, Compliance, and Ethical AI

As AI handles more sensitive data, contact centers embed security at multiple levels:

Voice biometrics for authentication (e.g., Nuance, Pindrop)

PII Redaction via entity recognition models

Audit Trails of AI decisions for compliance (especially in finance/healthcare)

Bias Monitoring Pipelines to detect model drift or demographic skew

Data governance frameworks like ISO 27001, GDPR, and SOC 2 compliance are standard in enterprise AI deployments.

Final Thoughts

AI in 2025 has moved far beyond simple automation. It now orchestrates entire contact center ecosystems—powering conversational agents, augmenting human reps, automating back-office workflows, and delivering predictive intelligence in real time.

The technical stack is increasingly cloud-native, model-driven, and infused with real-time analytics. For engineering teams, the focus is now on building scalable, secure, and ethical AI infrastructures that deliver measurable impact across customer satisfaction, cost savings, and employee productivity.

As AI models continue to advance, contact centers will evolve into fully adaptive systems, capable of learning, optimizing, and personalizing in real time. The revolution is already here—and it's deeply technical.

[lazeecomet]

The Story of KLogs: What happens when an Mechanical Engineer codes

Since i no longer work at Wearhouse Automation Startup (WAS for short) and havnt for many years i feel as though i should recount the tale of the most bonkers program i ever wrote, but we need to establish some background

WAS has its HQ very far away from the big customer site and i worked as a Field Service Engineer (FSE) on site. so i learned early on that if a problem needed to be solved fast, WE had to do it. we never got many updates on what was coming down the pipeline for us or what issues were being worked on. this made us very independent

As such, we got good at reading the robot logs ourselves. it took too much time to send the logs off to HQ for analysis and get back what the problem was. we can read. now GETTING the logs is another thing.

the early robots we cut our teeth on used 2.4 gHz wifi to communicate with FSE's so dumping the logs was as simple as pushing a button in a little application and it would spit out a txt file

later on our robots were upgraded to use a 2.4 mHz xbee radio to communicate with us. which was FUCKING SLOW. and log dumping became a much more tedious process. you had to connect, go to logging mode, and then the robot would vomit all the logs in the past 2 min OR the entirety of its memory bank (only 2 options) into a terminal window. you would then save the terminal window and open it in a text editor to read them. it could take up to 5 min to dump the entire log file and if you didnt dump fast enough, the ACK messages from the control server would fill up the logs and erase the error as the memory overwrote itself.

this missing logs problem was a Big Deal for software who now weren't getting every log from every error so a NEW method of saving logs was devised: the robot would just vomit the log data in real time over a DIFFERENT radio and we would save it to a KQL server. Thanks Daddy Microsoft.

now whats KQL you may be asking. why, its Microsofts very own SQL clone! its Kusto Query Language. never mind that the system uses a SQL database for daily operations. lets use this proprietary Microsoft thing because they are paying us

so yay, problem solved. we now never miss the logs. so how do we read them if they are split up line by line in a database? why with a query of course!

select * from tbLogs where RobotUID = [64CharLongString] and timestamp > [UnixTimeCode]

if this makes no sense to you, CONGRATULATIONS! you found the problem with this setup. Most FSE's were BAD at SQL which meant they didnt read logs anymore. If you do understand what the query is, CONGRATULATIONS! you see why this is Very Stupid.

You could not search by robot name. each robot had some arbitrarily assigned 64 character long string as an identifier and the timestamps were not set to local time. so you had run a lookup query to find the right name and do some time zone math to figure out what part of the logs to read. oh yeah and you had to download KQL to view them. so now we had both SQL and KQL on our computers

NOBODY in the field like this.

But Daddy Microsoft comes to the rescue

see we didnt JUST get KQL with part of that deal. we got the entire Microsoft cloud suite. and some people (like me) had been automating emails and stuff with Power Automate

This is Microsoft Power Automate. its Microsoft's version of Scratch but it has hooks into everything Microsoft. SharePoint, Teams, Outlook, Excel, it can integrate with all of it. i had been using it to send an email once a day with a list of all the robots in maintenance.

this gave me an idea

and i checked

and Power Automate had hooks for KQL

KLogs is actually short for Kusto Logs

I did not know how to program in Power Automate but damn it anything is better then writing KQL queries. so i got to work. and about 2 months later i had a BEHEMOTH of a Power Automate program. it lagged the webpage and many times when i tried to edit something my changes wouldn't take and i would have to click in very specific ways to ensure none of my variables were getting nuked. i dont think this was the intended purpose of Power Automate but this is what it did

the KLogger would watch a list of Teams chats and when someone typed "klogs" or pasted a copy of an ERROR mesage, it would spring into action.

it extracted the robot name from the message and timestamp from teams

it would lookup the name in the database to find the 64 long string UID and the location that robot was assigned too

it would reply to the message in teams saying it found a robot name and was getting logs

it would run a KQL query for the database and get the control system logs then export then into a CSV

it would save the CSV with the a .xls extension into a folder in ShairPoint (it would make a new folder for each day and location if it didnt have one already)

it would send ANOTHER message in teams with a LINK to the file in SharePoint

it would then enter a loop and scour the robot logs looking for the keyword ESTOP to find the error. (it did this because Kusto was SLOWER then the xbee radio and had up to a 10 min delay on syncing)

if it found the error, it would adjust its start and end timestamps to capture it and export the robot logs book-ended from the event by ~ 1 min. if it didnt, it would use the timestamp from when it was triggered +/- 5 min

it saved THOSE logs to SharePoint the same way as before

it would send ANOTHER message in teams with a link to the files

it would then check if the error was 1 of 3 very specific type of error with the camera. if it was it extracted the base64 jpg image saved in KQL as a byte array, do the math to convert it, and save that as a jpg in SharePoint (and link it of course)

and then it would terminate. and if it encountered an error anywhere in all of this, i had logic where it would spit back an error message in Teams as plaintext explaining what step failed and the program would close gracefully

I deployed it without asking anyone at one of the sites that was struggling. i just pointed it at their chat and turned it on. it had a bit of a rocky start (spammed chat) but man did the FSE's LOVE IT.

about 6 months later software deployed their answer to reading the logs: a webpage that acted as a nice GUI to the KQL database. much better then an CSV file

it still needed you to scroll though a big drop-down of robot names and enter a timestamp, but i noticed something. all that did was just change part of the URL and refresh the webpage

SO I MADE KLOGS 2 AND HAD IT GENERATE THE URL FOR YOU AND REPLY TO YOUR MESSAGE WITH IT. (it also still did the control server and jpg stuff). Theres a non-zero chance that klogs was still in use long after i left that job

now i dont recommend anyone use power automate like this. its clunky and weird. i had to make a variable called "Carrage Return" which was a blank text box that i pressed enter one time in because it was incapable of understanding /n or generating a new line in any capacity OTHER then this (thanks support forum).

im also sure this probably is giving the actual programmer people anxiety. imagine working at a company and then some rando you've never seen but only heard about as "the FSE whos really good at root causing stuff", in a department that does not do any coding, managed to, in their spare time, build and release and entire workflow piggybacking on your work without any oversight, code review, or permission.....and everyone liked it