#AI-powered

[jcmarchi]

Ganesh Shankar, CEO & Co-Founder of Responsive – Interview Series

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Ganesh Shankar, CEO & Co-Founder of Responsive – Interview Series

Ganesh Shankar, CEO and Co-Founder of Responsive, is an experienced product manager with a background in leading product development and software implementations for Fortune 500 enterprises. During his time in product management, he observed inefficiencies in the Request for Proposal (RFP) process—formal documents organizations use to solicit bids from vendors, often requiring extensive, detailed responses. Managing RFPs traditionally involves multiple stakeholders and repetitive tasks, making the process time-consuming and complex.

Founded in 2015 as RFPIO, Responsive was created to streamline RFP management through more efficient software solutions. The company introduced an automated approach to enhance collaboration, reduce manual effort, and improve efficiency. Over time, its technology expanded to support other complex information requests, including Requests for Information (RFIs), Due Diligence Questionnaires (DDQs), and security questionnaires.

Today, as Responsive, the company provides solutions for strategic response management, helping organizations accelerate growth, mitigate risk, and optimize their proposal and information request processes.

What inspired you to start Responsive, and how did you identify the gap in the market for response management software?

My co-founders and I founded Responsive in 2015 after facing our own struggles with the RFP response process at the software company we were working for at the time. Although not central to our job functions, we dedicated considerable time assisting the sales team with requests for proposals (RFPs), often feeling underappreciated despite our vital role in securing deals. Frustrated with the lack of technology to make the RFP process more efficient, we decided to build a better solution.  Fast forward nine years, and we’ve grown to nearly 500 employees, serve over 2,000 customers—including 25 Fortune 100 companies—and support nearly 400,000 users worldwide.

How did your background in product management and your previous roles influence the creation of Responsive?

As a product manager, I was constantly pulled by the Sales team into the RFP response process, spending almost a third of my time supporting sales instead of focusing on my core product management responsibilities. My two co-founders experienced a similar issue in their technology and implementation roles. We recognized this was a widespread problem with no existing technology solution, so we leveraged our almost 50 years of combined experience to create Responsive. We saw an opportunity to fundamentally transform how organizations share information, starting with managing and responding to complex proposal requests.

Responsive has evolved significantly since its founding in 2015. How do you maintain the balance between staying true to your original vision and adapting to market changes?

First, we’re meticulous about finding and nurturing talent that embodies our passion – essentially cloning our founding spirit across the organization. As we’ve scaled, it’s become critical to hire managers and team members who can authentically represent our core cultural values and commitment.

At the same time, we remain laser-focused on customer feedback. We document every piece of input, regardless of its size, recognizing that these insights create patterns that help us navigate product development, market positioning, and any uncertainty in the industry. Our approach isn’t about acting on every suggestion, but creating a comprehensive understanding of emerging trends across a variety of sources.

We also push ourselves to think beyond our immediate industry and to stay curious about adjacent spaces. Whether in healthcare, technology, or other sectors, we continually find inspiration for innovation. This outside-in perspective allows us to continually raise the bar, inspiring ideas from unexpected places and keeping our product dynamic and forward-thinking.

What metrics or success indicators are most important to you when evaluating the platform’s impact on customers?

When evaluating Responsive’s impact, our primary metric is how we drive customer revenue. We focus on two key success indicators: top-line revenue generation and operational efficiency. On the efficiency front, we aim to significantly reduce RFP response time – for many, we reduce it by 40%. This efficiency enables our customers to pursue more opportunities, ultimately accelerating their revenue generation potential.

How does Responsive leverage AI and machine learning to provide a competitive edge in the response management software market?

We leverage AI and machine learning to streamline response management in three key ways. First, our generative AI creates comprehensive proposal drafts in minutes, saving time and effort. Second, our Ask solution provides instant access to vetted organizational knowledge, enabling faster, more accurate responses. Third, our Profile Center helps InfoSec teams quickly find and manage security content.

With over $600 billion in proposals managed through the Responsive platform and four million Q&A pairs processed, our AI delivers intelligent recommendations and deep insights into response patterns. By automating complex tasks while keeping humans in control, we help organizations grow revenue, reduce risk, and respond more efficiently.

What differentiates Responsive’s platform from other solutions in the industry, particularly in terms of AI capabilities and integrations?

Since 2015, AI has been at the core of Responsive, powering a platform trusted by over 2,000 global customers. Our solution supports a wide range of RFx use cases, enabling seamless collaboration, workflow automation, content management, and project management across teams and stakeholders.

With key AI capabilities—like smart recommendations, an AI assistant, grammar checks, language translation, and built-in prompts—teams can deliver high-quality RFPs quickly and accurately.

Responsive also offers unmatched native integrations with leading apps, including CRM, cloud storage, productivity tools, and sales enablement. Our customer value programs include APMP-certified consultants, Responsive Academy courses, and a vibrant community of 1,500+ customers sharing insights and best practices.

Can you share insights into the development process behind Responsive’s core features, such as the AI recommendation engine and automated RFP responses?

Responsive AI is built on the foundation of accurate, up-to-date content, which is critical to the effectiveness of our AI recommendation engine and automated RFP responses. AI alone cannot resolve conflicting or incomplete data, so we’ve prioritized tools like hierarchical tags and robust content management to help users organize and maintain their information. By combining generative AI with this reliable data, our platform empowers teams to generate fast, high-quality responses while preserving credibility. AI serves as an assistive tool, with human oversight ensuring accuracy and authenticity, while features like the Ask product enable seamless access to trusted knowledge for tackling complex projects.

How have advancements in cloud computing and digitization influenced the way organizations approach RFPs and strategic response management?

Advancements in cloud computing have enabled greater efficiency, collaboration, and scalability. Cloud-based platforms allow teams to centralize content, streamline workflows, and collaborate in real time, regardless of location. This ensures faster turnaround times and more accurate, consistent responses.

Digitization has also enhanced how organizations manage and access their data, making it easier to leverage AI-powered tools like recommendation engines and automated responses. With these advancements, companies can focus more on strategy and personalization, responding to RFPs with greater speed and precision while driving better outcomes.

Responsive has been instrumental in helping companies like Microsoft and GEODIS streamline their RFP processes. Can you share a specific success story that highlights the impact of your platform?

Responsive has played a key role in supporting Microsoft’s sales staff by managing and curating 20,000 pieces of proposal content through its Proposal Resource Library, powered by Responsive AI. This technology enabled Microsoft’s proposal team to contribute $10.4 billion in revenue last fiscal year. Additionally, by implementing Responsive, Microsoft saved its sellers 93,000 hours—equivalent to over $17 million—that could be redirected toward fostering stronger customer relationships.

As another example of  Responsive providing measurable impact, our customer Netsmart significantly improved their response time and efficiency by implementing Responsive’s AI capabilities. They achieved a 10X faster response time, increased proposal submissions by 67%, and saw a 540% growth in user adoption. Key features such as AI Assistant, Requirements Analysis, and Auto Respond played crucial roles in these improvements. The integration with Salesforce and the establishment of a centralized Content Library further streamlined their processes, resulting in a 93% go-forward rate for RFPs and a 43% reduction in outdated content. Overall, Netsmart’s use of Responsive’s AI-driven platform led to substantial time savings, enhanced content accuracy, and increased productivity across their proposal management operations.

JAGGAER, another Responsive customer, achieved a double-digit win-rate increase and 15X ROI by using Responsive’s AI for content moderation, response creation, and Requirements Analysis, which improved decision-making and efficiency. User adoption tripled, and the platform streamlined collaboration and content management across multiple teams.

Where do you see the response management industry heading in the next five years, and how is Responsive positioned to lead in this space?

In the next five years, I see the response management industry being transformed by AI agents, with a focus on keeping humans in the loop. While we anticipate around 80 million jobs being replaced, we’ll simultaneously see 180 million new jobs created—a net positive for our industry.

Responsive is uniquely positioned to lead this transformation. We’ve processed over $600 billion in proposals and built a database of almost 4 million Q&A pairs. Our massive dataset allows us to understand complex patterns and develop AI solutions that go beyond simple automation.

Our approach is to embrace AI’s potential, finding opportunities for positive outcomes rather than fearing disruption. Companies with robust market intelligence, comprehensive data, and proven usage will emerge as leaders, and Responsive is at the forefront of that wave. The key is not just implementing AI, but doing so strategically with rich, contextual data that enables meaningful insights and efficiency.

Thank you for the great interview, readers who wish to learn more should visit Responsive,

[michaelespositostatenisland]

Michael Esposito Staten Island: Innovative AI Solutions for Influencer Marketing in the Digital Age

In the ever-evolving landscape of digital marketing, influencer marketing has emerged as a powerful strategy for brands to connect with their target audience and drive engagement. With the rise of social media platforms, influencers have become key players in shaping consumer preferences and purchasing decisions. Michael Esposito Staten Island — Influence in the Digital Age exemplifies this trend, highlighting how digital influencers can significantly impact marketing strategies and outcomes. However, as the digital space becomes increasingly saturated with content, brands are turning to innovative AI solutions to enhance their influencer marketing efforts and stay ahead of the curve.

AI-Powered Influencer Discovery

One of the biggest challenges brands face in influencer marketing is finding the right influencers to collaborate with. Traditional methods of influencer discovery often involve manual research and outreach, which can be time-consuming and inefficient. However, AI-powered influencer discovery platforms leverage advanced algorithms to analyze vast amounts of data and identify influencers who are the best fit for a brand's target audience and campaign objectives. Michael Esposito Staten Island: An Influencer Marketer Extraordinaire, exemplifies how effective influencer collaboration can transform marketing strategies. By harnessing the power of AI, brands can streamline the influencer discovery process and identify high-potential collaborators with greater accuracy and efficiency.

Predictive Analytics for Campaign Optimization

Once influencers have been identified and partnerships established, brands can leverage AI-powered predictive analytics to optimize their influencer marketing campaigns. Predictive analytics algorithms analyze historical campaign data, audience demographics, and engagement metrics to forecast the performance of future campaigns. By leveraging these insights, brands can make data-driven decisions about content strategy, audience targeting, and campaign optimization, maximizing the impact of their influencer collaborations and driving measurable results.

AI-Driven Content Creation

Content creation is a critical component of influencer marketing campaigns, and AI is revolutionizing the way brands create and optimize content for maximum impact. AI-powered content creation tools can generate personalized, high-quality content at scale, helping brands maintain a consistent brand voice and aesthetic across their influencer collaborations. From automated image and video editing to natural language processing for caption generation, AI-driven content creation tools empower brands to create compelling, on-brand content that resonates with their target audience and drives engagement.

Sentiment Analysis for Brand Monitoring

Influencer marketing campaigns can have a significant impact on brand perception, and it's essential for brands to monitor and manage their online reputation effectively. AI-powered sentiment analysis tools analyze social media conversations and user-generated content to gauge public sentiment towards a brand or campaign. By tracking mentions, sentiment trends, and key themes, brands can quickly identify and address any potential issues or negative feedback, allowing them to proactively manage their brand reputation and maintain a positive online presence.

Automated Performance Reporting

Measuring the success of influencer marketing campaigns is crucial for determining ROI and informing future strategies. However, manual performance reporting can be time-consuming and prone to human error. AI-powered analytics platforms automate the process of performance reporting by aggregating data from multiple sources, analyzing key metrics, and generating comprehensive reports in real-time. By providing brands with actionable insights into campaign performance, audience engagement, and ROI, AI-driven analytics platforms enable brands to optimize their influencer marketing efforts and drive continuous improvement.

In conclusion, as influencer marketing continues to evolve in the digital age, brands must leverage innovative AI solutions to stay competitive and maximize the impact of their campaigns. From AI-powered influencer discovery and predictive analytics to automated content creation and sentiment analysis, AI is revolutionizing every aspect of influencer marketing, enabling brands to connect with their target audience more effectively and drive measurable results. By embracing these innovative AI solutions, brands can unlock the full potential of influencer marketing and achieve success in the digital era.

[kanhasoft]

Why Mobile Brands Are Integrating AI Platforms Like Glance in 2025

In 2025, mobile brands are no longer just hardware providers; they are experience enablers. As digital behavior evolves, the integration of AI platforms like Glance is becoming a competitive necessity. Whether it’s offering hyper-personalized content or leveraging real-time data to predict user behavior, AI-powered user engagement is reshaping how brands communicate with users directly from their lock screens.

Let’s explore why the mobile industry is betting big on AI, especially platforms like Glance, and how it's changing the landscape of mobile experiences.

The Rise of AI-Powered Lock Screens

One of the most prominent shifts in mobile UX design has been the AI-powered lock screen. Platforms like Glance deliver content, ads, and personalized notifications right on the lock screen, minimizing the steps a user needs to take to engage with apps or services.

This form of AI-powered mobile UX design improves accessibility and delivers what users want before they even unlock their phone. Mobile brands recognize the value of this real estate, and AI makes it more intelligent than ever.

Why Lock Screens Matter

Increased Engagement: Users interact with their lock screens over 100 times a day.

Instant Personalization: Glance uses AI to predict user preferences and shows content accordingly.

Ad Monetization: Brands can now monetize lock screen real estate through AI in mobile advertising without intruding on the user experience.

Mobile AI Integration: Beyond the Basics

Modern mobile devices are packed with sensors, software, and processing power. But what differentiates one brand from another in 2025 is how they utilize mobile AI integration.

Benefits of Mobile AI Integration

Predictive Behavior Analysis: Anticipating what users need before they act.

Voice & Image Recognition: Seamless interaction via smart assistants and camera-based tools.

Battery & Performance Optimization: AI helps manage background processes, optimizing power and resources.

Glance exemplifies this by offering a dynamic feed that adjusts based on time of day, user mood, or past behavior—creating a seamless and engaging mobile environment.

Personalized Mobile Content is King

Personalization is no longer optional. Users expect experiences that are tailored to their tastes, habits, and needs. Platforms like Glance use AI to deliver personalized mobile content ranging from news and entertainment to shopping and learning.

Types of Personalized Content Delivered by Glance

News updates based on browsing history.

Short-form videos aligned with user interests.

App suggestions driven by contextual behavior.

Product recommendations powered by browsing and purchase data.

This level of personalization boosts engagement rates and increases app retention, making it a valuable asset for mobile brands.

AI in Mobile Advertising: A Smarter Approach

Traditional mobile ads often feel disruptive. AI changes this by making advertising contextual, relevant, and sometimes even welcome.

Advantages of AI in Mobile Advertising

Hyper-targeted Campaigns: Ads that reflect real-time needs.

Native Ad Integration: Seamless ad placements within the Glance lock screen.

Higher Conversion Rates: Personal relevance translates into better performance.

AI ensures that ads don’t feel like ads but like useful suggestions—a massive shift in mobile marketing dynamics.

AI-Powered User Engagement: Real-Time & Responsive

AI-powered user engagement goes beyond sending push notifications. It’s about understanding when, how, and why a user engages with content.

Platforms like Glance collect and process user signals to:

Engage users during high-attention moments.

Suggest meaningful actions (like booking a ride or ordering food).

Reduce churn by keeping the experience dynamic and responsive.

This deep engagement is why mobile brands prefer AI-based solutions over static content delivery methods.

How AI-Powered Mobile UX Design Impacts Brand Loyalty

Great UX has always driven brand loyalty, but AI takes it a step further. With AI-powered mobile UX design, mobile brands offer:

Instant loading speeds

Context-aware navigation

Adaptive themes and layouts

These features, powered by platforms like Glance, make smartphones feel like personalized ecosystems rather than generic gadgets.

Why Glance is Leading the AI Integration in Mobile Devices

Glance has positioned itself as a leader by focusing on micro-interactions that matter. Its success lies in:

Using AI to map user journeys from the lock screen.

Delivering content that increases screen time organically.

Enabling brands to connect meaningfully with consumers.

The platform serves as an example of how AI integration in mobile devices should be done—with intent, intelligence, and impact.

What This Means for the Future of Mobile UX

The adoption of AI platforms like Glance marks a turning point in how mobile brands think about user experience, engagement, and monetization.

Kanhasoft, as a leading AI development company, understands the importance of this shift. Our expertise in mobile AI integration, custom app development, and AI-powered solutions positions us to help businesses create next-gen mobile experiences.

Final Thoughts

The future of mobile is AI-first. From AI-powered lock screens to intelligent ad placements, mobile brands are redefining user engagement with platforms like Glance. In 2025, success will depend on how well a brand understands and implements AI into its mobile offerings.

Kanhasoft is ready to help you embrace this future.

Explore our AI-powered development services and transform your mobile brand today.

FAQs

Q1: What is Glance in mobile devices?

A: Glance is an AI-powered lock screen platform that delivers personalized content, ads, and app suggestions directly on your phone’s lock screen.

Q2: How does AI-powered user engagement work?

A: AI analyzes user behavior and preferences to deliver timely, relevant content and actions that improve retention and experience.

Q3: Why is mobile AI integration important in 2025?

A: With increasing competition, mobile brands need to offer smarter, personalized experiences. AI integration helps deliver that effectively.

Q4: Can Glance increase ad revenue for mobile brands?

A: Yes, by providing hyper-personalized and non-intrusive ad placements, Glance enhances user interaction and boosts conversions.

Q5: How can Kanhasoft help in AI development?

A: Kanhasoft offers tailored AI/ML solutions for mobile, web, and enterprise applications that focus on business outcomes and user experience.

[agseureinnovations]

INDIA MAKES HISTORY: WORLD'S 1ST GENOME-EDITED RICE VARIETIES LAUNCHED

India has made history by becoming the first country in the world to develop genome-edited rice varieties using 21st-century technology. On May 5, 2025, Agriculture Minister Shivraj Singh Chouhan launched these revolutionary rice varieties, created by leading scientists in Indian Council of Agricultural Research (ICAR) institutions.

These new varieties aim to help farmers grow more produce with less effort, even in challenging conditions like poor soil and harsh weather. They are also a big step toward Viksit Bharat (a developed India), as they will boost food security and support the growing population.

What are the new rice varieties?

1. DRR Dhan 100 (Kamala)

Derived from: Samba Mahsuri (a popular Indian rice)

Key features:

Matures 15-20 days earlier than regular varieties

Yields 25% more grain

Less risk of disease due to shorter growing period

This variety lets farmers harvest earlier and possibly grow an extra crop in a year, increasing their income and efficiency.

2. Pusa DST Rice 1

Key feature: Tolerant to salinity and alkalinity

Yields 30% more under saline soil conditions

Perfect for regions where salt-affected soils limit rice production

This variety gives hope to farmers in coastal and inland saline-prone areas, where normal rice struggles to grow.

Who developed these varieties?

These rice varieties were developed by leading researchers at ICAR institutes, which work under the Government of India to improve farming through science and technology.

The varieties have been tested and recommended to farmers in states such as Andhra Pradesh, Bihar, Karnataka, Telangana, Tamil Nadu, Uttar Pradesh, Chhattisgarh, Maharashtra, Madhya Pradesh  and West Bengal.

Why are these varieties important?

More food: Cultivating them on 5 million hectares can produce an extra 4.5 million tons of paddy.

Lower costs: Faster growth and higher yields reduce farming expenses.

Climate resilience: They can handle stressful soils and changing weather.

Better nutrition: Higher yields mean more rice to feed people.

According to ICAR, these genome-edited varieties will drive the Second Green Revolution in India, making farming smarter and more sustainable.

Checking Rice Quality is Easy with Agsure

As farmers adopt these high-yielding and climate-resilient rice varieties, tools like the Agsure Grain Quality Analyzer can help them measure grain quality quickly and accurately. Using AI-powered and machine learning, Agsure analyzes physical parameters like grain length, broken percentage, whiteness Index and quality grading within seconds—giving farmers, and millers clear insights to get the best market value for these new rice harvests.

Combining advanced seeds with smart grain analysis will empower farmers to improve both quantity and quality, strengthening India’s rice economy.

Conclusion

With DRR Dhan 100 Kamala and Pusa DST Rice 1, India is showing the world how modern science can solve age-old farming challenges. These new rice varieties will help farmers, consumers, and the nation grow stronger together. For more details visit here:  https://www.agsure.in/blog/our-blog-1/india-makes-history-world-s-1st-genome-edited-rice-varieties-launched-17

[cavenewstimestoday]

AI-Powered Rescue Dogs

A blur of golden fur and exuberance, the search and rescue dog bolts from a handler’s side and carves a wide arc through a patchy field in Missouri. The dog, who is part of an elite urban search-and-rescue team, knows what her duty is: Find a scent trail, locate the person at the other end of the odor, and alert her handler—guiding them to someone who might be lost, trapped, injured, or dead. But…

[visionaryvogues03]

How Robo-Advisors Are Changing the Game for Retail and Institutional Investors?

Robo-advisors can analyze vast amounts of data as there are significant technological shifts in machine learning, for the finance sector. Via the data analysis, it optimizes asset allocation, minimizes risks, & enhances returns. Investors can increasingly get investment insights from robo-advisors that are artificial-intelligence-enabled digitalized service agents. Investors often use mental shortcuts & use information based on past performances to make their investment decisions. Investors can only predict future market actions but these robots can give real-time insights. That does not mean they can’t go wrong, after all the stock market is an unpredictable game, isn’t it? 

Democratizing Investment Opportunities for Retail Investors

For decades, financial advisory services were primarily accessible to high-net-worth individuals who could afford personalized financial planning. Digital advisors have changed this by offering automated, algorithm-driven investment solutions to retail investors at a fraction of the cost.

Lower Costs and Fees: Traditional financial advisors charge management fees ranging from 1% to 2% of assets under management (AUM). In contrast, robo-advisors typically charge between 0.25% and 0.50%, making professional-grade investment management more accessible.

Personalized Portfolio Management: Modern AI investors use AI and machine learning to assess an investor’s risk tolerance, time horizon, and financial goals. Based on these inputs, they create customized investment portfolios that continuously adjust to market conditions.

Eliminating Emotional Bias: Human investors often make irrational decisions driven by fear or greed. AI investors remove emotional biases by following a disciplined, data-driven approach to investment decisions.

24/7 Accessibility: Unlike human advisors who work within business hours, digital advisors operate around the clock, ensuring investors can manage their portfolios anytime and anywhere.

Educational Tools: Many AI advisors now include educational resources, helping retail investors better understand financial markets and investment strategies.

How Institutional Investors Are Leveraging Robo-Advisors

While AI advisors initially gained traction among individual investors, institutional investors—including hedge funds, pension funds, and asset managers—are increasingly incorporating them into their strategies. Here’s how:

Enhanced Data Analytics: Institutional investors rely on vast amounts of data to make informed decisions. AI-powered robo-advisors analyze market trends, economic indicators, and risk factors to offer predictive insights that drive more effective investment strategies.

Automated Portfolio Rebalancing: Large-scale investment firms need to constantly adjust portfolios to optimize returns while managing risks. Fintech advisors can automatically rebalance portfolios based on pre-defined parameters, reducing human intervention and improving efficiency.

Cost Reduction and Scalability: Asset managers looking to reduce operational costs find AI investors invaluable. Automation allows firms to scale investment strategies across thousands of clients without the need for additional personnel.

Algorithmic Trading: Advanced wealth bots utilize machine learning and AI-driven algorithms to execute trades at optimal prices, enhancing portfolio returns.

Integration with Traditional Advisors: Many institutions are implementing hybrid models, combining AI-powered robo-advisors with human expertise for a more balanced investment approach.

Challenges and Limitations of Robo-Advisors

Despite their advantages, wealth bots come with their own set of challenges, particularly for institutional investors managing large portfolios.

Limited Human Insight: While AI-driven investment strategies rely on historical data and predictive analytics, they may struggle to respond effectively to unprecedented market events, such as geopolitical crises or sudden economic downturns.

Regulatory Concerns: Financial markets are highly regulated, and compliance is critical for institutional investors. Many algo-advisors are still navigating the complexities of regulatory requirements across different jurisdictions.

Customization Constraints: While AI wealth managers offer personalized investment strategies, they may not provide the level of customization required by large institutions that have highly specific investment mandates.

Security and Privacy Risks: As with any digital platform, robo-advisors must continually enhance their cybersecurity measures to protect investors' sensitive financial data.

The Future of Robo-Advisory Services

The rapid evolution of AI and machine learning is poised to further enhance the capabilities of robo-advisors. Future developments may include:

AI-Driven Hyper-Personalization: Advanced machine learning algorithms will enable fintech advisors to provide even more granular and customized investment solutions.

Blockchain and Smart Contracts: The integration of blockchain technology could enhance transparency and security in robo-advisory transactions, making them more attractive to institutional investors.

Hybrid Advisory Models: Many financial firms are already adopting hybrid models that combine human expertise with AI-driven insights, offering the best of both worlds to investors.

Expanding to Alternative Assets: As investment markets evolve, robo-advisors may incorporate alternative investments such as cryptocurrencies, real estate, and private equity into their offerings.

AI-Powered Risk Management: Future robo-advisors could leverage deep learning to anticipate and mitigate risks before they impact investment portfolios, ensuring greater stability.

Conclusion

The rise of robo-advisors is transforming the investment landscape for both retail and institutional investors. By providing cost-effective, data-driven, and automated investment solutions, they are making wealth management more accessible and efficient. While challenges remain, continued advancements in AI, blockchain, and hybrid advisory models will likely push wealth bots further into mainstream financial services. As technology evolves, businesses and investors alike must stay ahead of these innovations to maximize their financial growth and competitive advantage.

By embracing automation, financial institutions can reduce inefficiencies, mitigate risks, and offer more tailored investment solutions. Whether for an individual investor looking for low-cost financial planning or an institutional player seeking sophisticated algorithmic strategies, auto-investors represent the future of investment management. The firms that successfully integrate these AI-driven solutions will be well-positioned to lead in the ever-evolving financial ecosystem.

Uncover the latest trends and insights with our articles on Visionary Vogues

[gappeo]

Building a Strong Employer Brand Through Smarter Hiring Strategies

In today’s competitive job market, attracting top talent and maintaining a strong employer brand is crucial for long-term success. Organizations need to focus not just on hiring employees but on creating a reputation that draws in the best candidates. One of the most effective ways to do this is by implementing smarter hiring strategies powered by data-driven recruitment and AI-powered hiring. These strategies streamline the hiring process, reduce bias, and ensure that candidates align with the company’s culture and values, thereby enhancing the employer brand.

What is Employer Branding?

Employer branding refers to the reputation an organization holds as an employer. A strong employer brand helps businesses attract top talent and improve employee retention. Companies known for a positive work environment and fair hiring practices are viewed more favorably, leading to a higher quality of applicants and a stronger workforce.

How Smarter Hiring Strategies Enhance Your Employer Brand

Data-Driven Recruitment and AI-Powered Hiring are two key strategies that can elevate your employer brand by ensuring a more efficient, unbiased, and engaging recruitment process.

1. Data-Driven Recruitment

Data-driven recruitment involves using analytics to inform hiring decisions. By leveraging historical data on employee performance and qualifications, companies can better understand which candidate traits lead to success.

Improved Candidate Selection: Data helps identify candidates who are likely to succeed in your company.

Enhanced Candidate Experience: Personalizing the hiring process improves candidate satisfaction and fosters a positive perception of your organization.

Bias Reduction: Data allows for more objective hiring decisions, creating a more inclusive and diverse workforce.

2. AI-Powered Hiring

AI tools, such as chatbots and predictive analytics, automate and enhance key stages of the hiring process. These tools help organizations engage with candidates more efficiently while ensuring better hiring decisions.

Efficiency and Speed: AI accelerates the recruitment process by quickly screening resumes and handling communication.

Personalized Candidate Engagement: AI provides tailored job recommendations, improving the candidate experience.

Bias-Free Hiring: AI ensures hiring decisions are based solely on qualifications and fit, reducing human bias.

Improving Retention Through Smarter Hiring

A strong employer brand isn’t just about attracting top talent; it’s also about retaining them. Smarter hiring strategies help ensure that new hires are a good fit for the company culture, which contributes to higher job satisfaction and longer tenure.

Better Cultural Fit: Data and AI help hire individuals who align with company values and culture, leading to higher employee retention.

Employee Satisfaction: A fair, transparent hiring process fosters a sense of belonging and trust among employees, improving their overall satisfaction and engagement.

[leonbasinwriter]

GTM in 2025 – The Sales Strategy No One Talks About

@leonbasinwriter Cybersecurity sales is changing. Fast. Buyers don’t trust traditional pitches. AI is reshaping how decisions are made. Vendors who rely on outdated playbooks will struggle to close deals. In 2025, GTM isn’t just about features and trust—it’s about timing, storytelling, and AI-driven execution. Businesses don’t buy security. They buy certainty.  The question is, are you…

[inklingdd]

INKLING AI – The Future of Smart Conversations!

Artificial intelligence has transformed the way we interact with technology, and conversational AI is at the forefront of this revolution. One of the most promising advancements in this space is Inkling AI, a powerful AI-driven system designed to facilitate smart, seamless conversations. But what makes Inkling AI different? Why is it being hailed as the future of intelligent conversations? Let’s dive into the world of Inkling AI and explore its capabilities, applications, and what it means for the future.

What is Inkling AI?

Inkling AI is a next-generation artificial intelligence system engineered to enhance human-machine interactions. It utilizes advanced machine learning algorithms, natural language processing (NLP), and deep learning to understand, interpret, and generate human-like responses. Unlike traditional chatbots, Inkling AI offers more fluid, dynamic, and context-aware conversations.

How Does Inkling AI Work?

Inkling AI operates on multiple sophisticated AI technologies to ensure accurate and meaningful interactions:

1. Natural Language Processing (NLP)

Enables the AI to understand user intent, sentiment, and context.

Helps in breaking down complex queries into simpler components for better comprehension.

2. Machine Learning Algorithms

Continuously learns from interactions to improve accuracy and efficiency.

Adapts to user preferences and refines responses over time.

3. Contextual Awareness

Retains past interactions to maintain conversational flow.

Understands context-based variations for a more human-like experience.

Key Features of Inkling AI

1. Human-like Conversations

Inkling AI can hold conversations that feel natural and engaging, making it an excellent tool for customer support, personal assistants, and virtual companions.

2. Multi-language Support

It can communicate in multiple languages, breaking language barriers and making AI interactions more inclusive.

3. Adaptive Learning

The AI learns from interactions and improves over time, ensuring that responses become more refined and personalized.

4. Sentiment Analysis

Inkling AI can detect emotions in text and respond accordingly, making interactions more empathetic and contextually relevant.

5. Seamless Integration

It can be integrated into various platforms, including websites, mobile apps, and social media, providing a smooth and accessible user experience.

Applications of Inkling AI

1. Customer Support

Reduces response time by handling multiple queries simultaneously.

Provides 24/7 support with accurate and instant solutions.

2. Virtual Assistants

Helps users manage tasks, set reminders, and retrieve information efficiently.

Enhances productivity by automating repetitive activities.

3. E-commerce and Sales

Assists customers in finding products and answering inquiries.

Offers personalized recommendations based on user behavior.

4. Healthcare Assistance

Provides preliminary health advice and symptom analysis.

Helps schedule appointments and remind patients of medication timings.

5. Educational Support

Acts as a tutor for students by answering questions and explaining concepts.

Helps in language learning and test preparations.

How Inkling AI is Changing the AI Landscape

Inkling AI stands out in the AI industry because of its unique ability to create meaningful and intelligent conversations. Unlike traditional AI chatbots that often provide robotic and generic responses, Inkling AI understands user intent, making interactions more natural and effective.

Future of Inkling AI

The future of Inkling AI looks promising as advancements in AI technology continue to push the boundaries of smart conversations. With continuous improvements in NLP, machine learning, and deep learning, we can expect:

More human-like interactions

Better emotional intelligence in AI responses

Improved security and privacy measures

Expanded industry applications

Conclusion

Inkling AI represents the future of smart conversations by bridging the gap between human interactions and artificial intelligence. Its ability to understand, learn, and respond in a natural manner makes it a game-changer in various industries. As technology continues to evolve, we can expect Inkling AI to redefine the way we communicate with machines, making conversations more intelligent, seamless, and engaging.

FAQs

1. How is Inkling AI different from traditional chatbots?

Unlike traditional chatbots, Inkling AI offers advanced contextual understanding, adaptive learning, and sentiment analysis, making interactions more dynamic and human-like.

2. Can Inkling AI be used for business applications?

Yes! Inkling AI is widely used in customer support, sales, e-commerce, and healthcare to enhance user engagement and improve efficiency.

3. Does Inkling AI support multiple languages?

Yes, Inkling AI is designed to support multiple languages, making it accessible to a global audience.

4. How secure is Inkling AI?

Security is a top priority, and Inkling AI employs encryption and data protection measures to ensure user data privacy.

5. What is the future potential of Inkling AI?

The future of Inkling AI includes better conversational abilities, enhanced emotional intelligence, and expanded applications in various industries.

[jcmarchi]

Stackpack Secures $6.3M to Reinvent Vendor Management in an AI-Driven Business Landscape

New Post has been published on https://thedigitalinsider.com/stackpack-secures-6-3m-to-reinvent-vendor-management-in-an-ai-driven-business-landscape/

Stackpack Secures $6.3M to Reinvent Vendor Management in an AI-Driven Business Landscape

In a world where third-party tools, services, and contractors form the operational backbone of modern companies, Stackpack has raised $6.3 million to bring order to the growing complexity.

Led by Freestyle Capital, the funding round includes support from Elefund, Upside Partnership, Nomad Ventures, Layout Ventures, MSIV Fund, and strategic angels from Intuit, Workday, Affirm, Snapdocs, and xAI.

The funding supports Stackpack’s mission to redefine how businesses manage their expanding vendor networks—an increasingly vital task as organizations now juggle hundreds or even thousands of external partners and platforms.

Turning Chaos into Control

Founded in 2023 by Sara Wyman, formerly of Etsy and Affirm, Stackpack was built to solve a problem she knew too well: modern companies are powered by vendors, yet most still track them with outdated methods—spreadsheets, scattered documents, and guesswork. With SaaS stacks ballooning and AI tools proliferating, unmanaged vendors become silent liabilities.

“Companies call themselves ‘people-first,’ but in reality, they’re becoming ‘vendor-first,’” said Wyman. “There are often 6x more vendors than employees. Yet there’s no system of record to manage that shift—until now.”

Stackpack gives finance and IT teams a unified, AI-powered dashboard that provides real-time visibility into vendor contracts, spend, renewals, and compliance risks. The platform automatically extracts key contract terms like auto-renewal clauses, flags overlapping subscriptions, and even predicts upcoming renewals buried deep in PDFs.

AI That Works Like a Virtual Vendor Manager

Stackpack’s Behavioral AI Engine acts as an intelligent assistant, surfacing hidden cost-saving opportunities, compliance risks, and critical dates. It not only identifies inefficiencies—it takes action, issuing alerts, initiating workflows, and providing recommendations across the vendor lifecycle.

For instance:

Renewal alerts prevent surprise charges.

Spend tracking identifies underused or duplicate tools.

Contract intelligence extracts legal and pricing terms from uploads or integrations with tools like Google Drive.

Approval workflows streamline onboarding and procurement.

This brings the kind of automation once reserved for enterprise procurement platforms like Coupa or SAP to startups and mid-sized businesses—at a fraction of the cost.

A Timely Solution for a Growing Problem

Vendor management has become a boardroom issue. As more companies shift budgets from headcount to outsourced services, compliance and financial oversight have become harder to maintain. Stackpack’s early traction is proof of demand: just months after launch, it’s managing over 10,500 vendors and $510 million in spend across more than 50 customers, including Every Man Jack, Rho, Density, HouseRx, Fexa, and ZeroEyes.

“The CFO is the one left holding the bag when things go wrong,” said Brandon Lee, Accounting Manager at BizzyCar. “Stackpack means we don’t have to cross our fingers every quarter.”

Beyond Visibility: Enabling Smarter Vendor Decisions

Alongside its core platform, Stackpack is launching Requests & Approvals, a lightweight tool to simplify vendor onboarding and purchasing decisions—currently in beta. The feature is already attracting customers looking for faster, more agile alternatives to traditional procurement systems.

With a long-term vision to help companies not only manage but discover and evaluate vendors more strategically, Stackpack is laying the groundwork for a smarter, interconnected vendor ecosystem.

“Every vendor decision carries legal, financial, and security consequences,” said Dave Samuel, General Partner at Freestyle Capital. “Stackpack is building the intelligent infrastructure to manage these relationships proactively.”

The Future of Vendor Operations

As third-party ecosystems grow in size and complexity, Stackpack aims to transform vendor operations from a liability into a competitive advantage. Its AI-powered approach gives companies a modern operating system for vendor management—one that’s scalable, proactive, and deeply integrated into finance and operations.

“This isn’t just about cost control—it’s about running a smarter company,” said Wyman. “Managing your vendors should be as strategic as managing your talent. We’re giving companies the tools to make that possible.”

With fresh funding and a rapidly expanding customer base, Stackpack is poised to become the new standard for how modern businesses manage the partners powering their growth.

[nicheybay]

Trending products play a crucial role in dropshipping as they drive demand and fast sales. With NicheBay, an AI-powered platform, discovering trending products for dropshipping is simplified, allowing sellers to stay ahead of market shifts. By focusing on the latest popular items, you can attract customers and boost your business performance with ease. This platform helps you tap into trends effortlessly, maximizing your success.

[intellectra]

Streamline Your Coaching, Content, and Community with a Seamless, AI-Powered Platform

Transform your passion into a thriving business with Intellectra – the all-in-one, AI-powered platform that simplifies every step of coaching, content creation, and community building. From seamless course creation to personalized community engagement, Intellectra empowers you to connect with your audience, scale your offerings, and elevate your impact like never before.

[kanhasoft]

AI Professional Services: Transforming Business Operations with Custom Software Development

Welcome to the era of AI (where acronyms outnumber coffee breaks) — and yes, we’re living in it. Businesses today are on the hunt for smarter, faster, and more scalable ways to operate. Enter AI professional services, a trend that has quickly shifted from tech buzzword to business lifeline. And when paired with custom software development, it’s not just transformation — it’s evolution with a turbo boost.

At Kanhasoft, we’ve seen firsthand how tailored AI solutions (with a healthy dose of code and caffeine) are reshaping operations across industries. From automating repetitive tasks to offering real-time insights, custom AI-infused applications are setting the new standard for operational excellence.

The AI + Custom Software Combo: Like Peanut Butter and Productivity

Let’s be real: off-the-shelf software can be about as helpful as a chocolate teapot when your business needs are unique. That’s why custom solutions matter. Add AI into the mix, and you get software that doesn’t just work — it learns, adapts, and improves over time.

We recently worked with a mid-sized logistics firm that was drowning in paperwork and manual processes. After implementing an AI-powered ERP system tailored to their workflows, they reduced admin time by 70%. No magic, just smart development (and okay, a bit of wizardry on our backend team’s part).

Our experience with a healthcare startup was equally telling — they were manually reviewing hundreds of patient forms. We created a custom web application integrated with AI that could scan, classify, and highlight anomalies in real-time. Not only did it slash hours off their review time, but it also reduced human error by 90%. Results like these remind us that technology done right doesn’t just support businesses — it transforms them.

Real-World Impact: Efficiency, Accuracy & A Lot Less Guesswork

Custom AI solutions are changing the way departments function:

HR teams are using AI for recruitment analytics (no more playing resume roulette).

Sales departments benefit from predictive lead scoring and AI-powered CRM systems.

Inventory managers love demand forecasting tools that actually… well, forecast.

We’ve also helped finance companies integrate fraud detection AI into their mobile apps, giving users real-time alerts and saving companies thousands in potential losses. One client saw a 60% drop in flagged transaction errors within a month of deployment. It was almost enough to make accountants smile (almost).

In short? AI + custom development = less manual work, fewer mistakes, and more time for innovation (or lunch breaks).

Why Not Just Use ChatGPT for Everything?

Yes, we get asked this a lot. While tools like ChatGPT are handy, they’re not exactly built to manage your CRM, automate your invoices, or integrate with your warehouse sensors. That’s where AI professional services come in. We help build custom web applications and mobile apps that use AI not just for novelty but for actual business value.

Think of it as the difference between buying a robot that can do a backflip (cool, but useless at invoicing) and one that learns your workflows and helps reduce human error.

AI Across Industries: From Retail to Real Estate

One of our clients in eCommerce (we’ll call them “MegaMart” because they asked us not to use their real name) used our custom Amazon seller tools enhanced with AI to automatically adjust pricing based on competitor activity and market demand. The result? A 35% bump in profit margins within 90 days.

Then there’s our real estate client who used AI-powered chatbots to pre-qualify leads and schedule showings — cutting lead response time from hours to seconds.

In the logistics sector, we developed an AI system that could optimize delivery routes based on weather, traffic, and delivery urgency. The result? A 25% improvement in delivery efficiency and a significant reduction in fuel costs.

And in education, we created a mobile app for a tutoring company that uses machine learning to customize study paths for students based on their progress. Engagement went up. Dropout rates? Down. Happy parents? You bet.

No matter your industry, if there’s data (and we guarantee there is), there’s a way to turn it into smarter decisions.

Security is another concern — AI systems can be powerful, but they need guardrails. We build ours with built-in compliance checks, encryption, and role-based access to keep your data safe and sound. No wild algorithms running amok here.

We always recommend starting small. Identify one key process, integrate AI there, and scale as the ROI becomes clear. Trust us, once the results roll in, scaling becomes the obvious next step.

Kanhasoft’s AI Professional Services

We approach AI with purpose — not just for the sake of tech novelty. Whether you need a new custom CRM, want to integrate machine learning into your mobile app, or build AI-powered dashboards for your ERP, we take the time to understand your operations, goals, and users.

And yes, we do it with a sense of humor. (One client actually said, “You made AI implementation… fun?” We’ll take it.)

Our process involves:

Deep discovery sessions (with lots of coffee).

Collaborative prototyping.

Agile development with regular check-ins.

Integration, training, and support.

And most importantly, we never leave you hanging with a half-built solution.

FAQs

Q1: What kind of businesses benefit most from AI professional services?  Any business with repetitive tasks, large volumes of data, or complex decision-making. That includes retail, logistics, healthcare, real estate, and finance — to name a few.

Q2: How long does it take to build a custom AI solution?  It depends on the complexity. Simple automations can take weeks, while full-fledged ERP or CRM systems with AI can take a few months.

Q3: Do I need to have clean data to use AI?  Clean-ish. While clean data helps, our development process includes data preparation and cleansing as part of the AI integration.

Q4: Can existing systems be upgraded with AI?  Absolutely. Many of our projects involve integrating AI into legacy systems with smart APIs and microservices.

Q5: Isn’t AI expensive?  Not necessarily. When done right, AI saves more than it costs — through efficiency, automation, and better decision-making.

Q6: What platforms do you support for custom software development?  We develop for web, mobile (iOS and Android), desktop, and cloud platforms — using modern tech stacks that ensure scalability and security.

Q7: Can Kanhasoft help with AI strategy too?  Definitely. We don’t just build solutions; we help businesses map out their AI journey with step-by-step planning.

Conclusion

AI isn’t just a shiny tech trend — it’s a real-world business enhancer when paired with smart, custom-built software. Whether you’re looking to revamp your CRM, automate your inventory, or simply get rid of the 17 spreadsheets you’re currently juggling, AI professional services are your new best friend.

At Kanhasoft, we’re not just coders — we’re your tech partners in navigating the next wave of digital transformation. So if you’re ready to let software do the heavy lifting while you focus on scaling your business, let’s talk.

[eduttechera]

AI-Powered Interactive Content for Education: Transforming Learning for the Future

Artificial Intelligence (AI) is revolutionizing various industries, and education is no exception. The integration of AI-powered interactive education is changing the way students learn, educators teach, and institutions operate. With AI-powered personalized learning platforms, AI-driven teaching methods, and smart content creation, the future of AI in education looks promising.

The Rise of AI-Powered Interactive Education

AI-powered interactive education refers to the use of artificial intelligence to create engaging, adaptive, and personalized learning experiences. This approach leverages AI algorithms to analyze student performance, tailor content to individual needs, and provide instant feedback, making learning more effective and efficient.

Benefits of AI in Education

The adoption of AI in education offers numerous benefits:

Personalized Learning — AI-powered personalized learning platforms analyze students’ strengths and weaknesses and adapt content accordingly.

Instant Feedback — AI provides immediate feedback, helping students correct mistakes and improve learning outcomes.

Enhanced Engagement — Interactive content, such as gamified lessons and virtual simulations, keeps students engaged.

Efficiency for Educators — AI automates administrative tasks like grading and scheduling, allowing educators to focus on teaching.

Accessibility — AI-powered tools provide support for students with disabilities and language barriers.

AI-Powered Personalized Learning Platform Project

A key innovation in AI-powered interactive education is personalized learning platforms. These platforms utilize AI algorithms to customize learning experiences for each student, ensuring they receive instruction tailored to their unique needs and learning pace.

How AI Personalizes Learning

AI-powered personalized learning platforms function by:

Analyzing Data — Tracking student performance to identify areas of improvement.

Adaptive Learning Paths — Adjusting difficulty levels based on student progress.

Smart Content Recommendations — Suggesting relevant materials to enhance understanding.

Real-Time Support — Offering AI-driven tutoring and feedback.

A successful AI-powered personalized learning platform project integrates machine learning models, natural language processing (NLP), and predictive analytics to make education more effective and accessible.

Teaching with AI: A Game Changer for Educators

Educators are leveraging AI to transform traditional teaching methods. AI-powered tools assist teachers in various ways:

Automated Grading — AI reduces the workload by grading assignments and tests efficiently.

Classroom Management — AI-powered chatbots handle student inquiries and administrative tasks.

Smart Content Creation — AI generates quizzes, lesson plans, and interactive study materials.

Virtual Tutors — AI-powered tutoring systems provide additional support to students.

Predictive Analytics — AI predicts student performance trends and helps teachers intervene when needed.

Best AI Tools for Teaching

Some popular AI-powered tools that enhance teaching include:

Google Classroom — Integrates AI to automate administrative tasks.

Socratic by Google — Uses AI to help students with homework.

Quillionz — AI-powered tool for generating quizzes and assessments.

Century Tech — AI-driven personalized learning platform.

Artificial Intelligence in Education: A New Era

Artificial intelligence in education is not just about automating tasks; it is reshaping the way knowledge is imparted and absorbed. AI is helping to:

Improve learning outcomes with adaptive learning algorithms.

Enhance creativity through AI-powered content creation tools.

Provide real-time language translation for global education.

Support teachers with AI-driven insights into student progress.

Foster collaboration with AI-powered virtual classrooms.

The Future of AI in Education

The future of AI in education is incredibly promising. Some key trends to watch for include:

1. AI-Driven Virtual Classrooms

AI-powered virtual classrooms will offer immersive and interactive learning experiences, enabling students to learn from anywhere in the world.

2. AI-Powered Chatbots for Learning Assistance

AI chatbots will become more sophisticated, providing instant tutoring, answering student queries, and offering personalized learning recommendations.

3. Gamification and AI in Learning

AI will drive gamified learning experiences, making education more engaging and fun. Gamification elements like leaderboards, challenges, and AI-driven feedback loops will enhance learning.

4. AI-Generated Learning Materials

AI will create dynamic, adaptive study materials, such as AI-generated textbooks, quizzes, and multimedia lessons tailored to individual learning needs.

5. Ethical AI in Education

As AI becomes more integrated into education, ethical considerations like data privacy, bias in AI algorithms, and responsible AI use will become critical areas of focus.

AI-Powered Interactive Content: Transforming Learning Experiences

AI-powered interactive content is at the forefront of the education revolution. Interactive content includes:

AI-driven simulations — Virtual reality (VR) and augmented reality (AR) simulations for practical learning.

Adaptive e-learning modules — AI adjusts content difficulty based on student comprehension.

Voice and Chat AI Tutors — AI-powered virtual assistants for personalized guidance.

AI-Powered Assessments — Smart quizzes that analyze student responses and provide tailored feedback.

Implementing AI-Powered Interactive Content in Education

For institutions and educators looking to integrate AI-powered interactive content, here are actionable steps:

Adopt AI-Powered Learning Platforms — Use tools like edutechera.com to integrate AI in your teaching methods.

Leverage AI-Driven Analytics — Use AI-powered insights to track student performance.

Invest in AI Training for Educators — Provide teachers with AI literacy training.

Use AI for Content Personalization — Implement AI tools that adjust learning materials based on student needs.

Incorporate Interactive AI Tools — Engage students with AI-powered simulations, gamified learning, and virtual tutors.

Conclusion

AI-powered interactive education is revolutionizing the learning landscape. With AI-powered personalized learning platforms, teaching with AI, and the continuous evolution of artificial intelligence in education, students and educators alike benefit from more efficient, engaging, and effective learning experiences.

As we move toward the future of AI in education, institutions must embrace AI-powered interactive content to enhance learning outcomes and prepare students for the digital age.

To stay updated with the latest in AI-powered education, visit edutechera.com and explore the future of learning today!