Ooma Launches POTSTracker.com to Help Organizations Track and Manage POTS Line Discontinuance

February 17, 2026

AI-Powered Platform Provides Visibility into Copper Network Retirement and Legacy Voice Service Risk

Ooma, Inc., a provider of advanced communications services for businesses and consumers, announced the launch of POTSTracker.com, an AI-powered monitoring and analysis platform designed to help organizations navigate the complex landscape of legacy voice service discontinuance. As telecommunications carriers across the United States accelerate the retirement of traditional copper-based Plain Old Telephone Service (POTS) lines, POTSTracker.com gives enterprises and multi-site organizations the visibility and planning tools needed to support business continuity.

“The retirement of copper-based voice services is no longer a future concern—it’s a present-day operational risk for organizations that depend on POTS for critical systems,” said Chris Burgy, senior vice president, corporate development at Ooma.

POTSTracker.com is one of the first centralized platforms focused specifically on tracking POTS discontinuance activity and related risk signals across geographies and carriers.

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Regulatory and market shifts have accelerated copper network retirement. In recent years, the Federal Communications Commission (FCC) reduced legacy copper service obligations, giving carriers greater latitude to discontinue POTS lines and retire legacy infrastructure. As a result, discontinuance notices and wire center shutdowns are increasing across the country. Many organizations still rely on POTS lines for mission-critical applications, including fire alarm systems, elevator phones, security systems, and point-of-sale terminals, often without centralized visibility into where they are exposed or when service may be withdrawn.

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“The retirement of copper-based voice services is no longer a future concern—it’s a present-day operational risk for organizations that depend on POTS for critical systems,” said Chris Burgy, senior vice president, corporate development at Ooma. “Many organizations don’t realize they are in a discontinuance path until they receive notice or experience a disruption. With POTSTracker.com, we’re giving enterprises the visibility, intelligence, and confidence they need to stay ahead of carrier discontinuance activity, protect essential services, and plan transitions on their own terms—before outages and surprises occur.”

POTSTracker.com AI-powered capabilities from Ooma include:

Real-Time FCC Discontinuance Monitoring: Automated tracking of carrier discontinuance notices with geographic mapping of affected areas
Risk Assessment & Auditing: Auditing tools with criticality scoring for POTS-dependent assets
Watch List Management: Priority location tracking with automated alerts when new filings affect monitored areas
POTS Line Inventory Management: Centralized inventory tracking with carrier and cost visibility
Pricing Intelligence: Aggregated pricing data to help inform migration planning
Multi-Tenant Architecture: Enterprise-ready design supporting partners, resellers, and customer organizational structures

With discontinuance activity increasing and timelines tightening, proactive visibility is becoming essential for organizations that still depend on legacy copper lines.

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JPLoft Strengthens Its Web Development Services to Support Digital Growth for Businesses

MTS Staff Writer

February 17, 2026

Newsroom PR Aligns Leadership Around LLM Visibility

JPLoft enhances its web development services, empowering businesses with advanced technologies for faster digital growth.

JPLoft announced the expansion of its web development services to help businesses achieve scalable and long-term digital growth. The enhanced service offering focuses on building flexible, high-performing web solutions that support modern business goals.

We aim to empower businesses with future-ready web solutions that drive growth, enhance customer experiences, and reflect our commitment to innovation and long-term value.”

— Rahul Sukhwal

With this expansion, JPLoft aims to help startups, businesses, and enterprises create reliable digital platforms that grow alongside their operations.

As businesses increasingly rely on digital channels to connect with customers, manage operations, and deliver services, the need for scalable and future-ready web solutions has become more important than ever.

JPLoft’s strengthened web development services to support this shift by combining smart planning, user-focused design, and modern technology to deliver measurable results.

Market Demand for Scalable Web Development

Nowadays, businesses face constant pressure to scale their online presence quickly and smoothly. Websites and web platforms are no longer simple information pages.

They are now central tools for sales, customer engagement, data handling, and service delivery. As businesses grow, many struggle with slow websites, limited features, and systems that cannot handle increased traffic or data.

Market demand for scalable web development has grown as companies expand into new regions and adopt cloud-based operations. Another challenge businesses face is adapting to changing customer expectations.

Users expect fast loading times, smooth navigation, mobile-friendly design, and secure experiences. Scalable web development helps solve these challenges by building flexible systems that adapt to growth and user behavior over time.

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JPLoft’s Expanded Web Development Capabilities

To meet growing market demands, JPLoft, as a custom web development company, has expanded its capabilities with a strong focus on scalability, performance, and long-term value.

► Custom and Scalable Web Solutions

The company develops custom web solutions tailored to specific business needs.

Instead of using one-size-fits-all approaches, the team focuses on understanding business goals, user needs, and plans.

This allows the creation of web platforms that scale smoothly as user numbers, data, and features increase.

► Secure, Performance-Driven Development

Security and performance are built into every stage of development.

JPLoft follows best practices to protect user data, prevent security risks, and ensure stable system performance.

Optimized coding, efficient data handling, and strong security layers help deliver fast and reliable web experiences.

► Cloud-Ready and Future-Proof Architecture

The expanded services include cloud-ready architectures that support flexibility and easy scaling.

Cloud-based development helps businesses manage resources better, reduce downtime, and improve system reliability.

These future-proof designs allow businesses to add new features or expand operations without major system changes.

Through these capabilities, JPLoft ensures that web platforms remain strong, flexible, and ready for long-term growth.

Technologies and Development Approach

JPLoft’s expanded web development services are supported by modern technologies and a clear development approach that aligns with business goals.

● Modern Frameworks and Tech Stack

The company uses reliable and widely adopted frameworks such as React.js, Angular, and Vue.js for front-end development. However, this ensures fast performance and smooth user experiences.

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For back-end development, the company leverages Node.js, Laravel, Django, and Ruby on Rails to create secure and scalable server-side systems. JPLoft also uses RESTful APIs and GraphQL to enable smooth integration with third-party tools and services.

To support scalability and long-term usability, the tech stack includes cloud platforms such as AWS, Microsoft Azure, and Google Cloud, along with databases like MySQL, PostgreSQL, and MongoDB.

Businesses can hire web developers from JPLoft to reduce technical risk while keeping their web platforms easy to update and future-ready.

● Agile and Business-Aligned Development Methodology

JPLoft follows an agile development approach that allows continuous improvement and quick adjustments. Projects are developed in phases, with regular reviews and updates.

This method helps businesses stay involved in the process and ensures that the final product aligns with real business needs. The development approach focuses on collaboration, clear communication, and practical solutions.

By aligning technical decisions with business goals, JPLoft delivers web platforms that support growth, efficiency, and user satisfaction.

Integration Capabilities and Third-Party System Support

Modern businesses use many tools to manage sales, payments, inventory, marketing, and customer data.

JPLoft builds web solutions that integrate easily with third-party systems. They help businesses manage everything from one connected platform.

1) CRM Integration

Customer Relationship Management (CRM) systems help businesses manage leads, customers, and sales processes. JPLoft integrates web platforms with popular CRM tools so that customer data flows smoothly between systems.

With proper CRM integration, businesses can:

• Track leads in real time
• Improve customer communication
• Manage follow-ups easily
• View customer history in one place

This creates a smooth experience for both the business and the customer.

2) Payment Gateway Integration

For businesses that sell products or services online, secure payment processing is essential. JPLoft integrates trusted payment gateways into web platforms to ensure safe and smooth transactions.

Benefits of payment gateway integration include:

• Secure online transactions
• Fast payment processing
• Support for multiple payment options
• Better customer trust

A smooth checkout process also improves conversion rates and reduces cart abandonment.

3) ERP System Integration

Enterprise Resource Planning (ERP) systems help businesses manage core operations such as inventory, accounting, supply chain, and human resources.

For example, when a product is sold online, inventory levels can update automatically in the ERP system. Financial data can also sync in real time, reducing manual work and errors.

ERP integration helps businesses:

• Improve operational efficiency
• Reduce duplicate data entry
• Maintain accurate records
• Manage resources better

This creates a unified system where different departments stay aligned.

4) API Integration

APIs allow different systems and applications to communicate with each other. JPLoft uses secure and well-structured APIs to connect web platforms with third-party services.

Through API integration, businesses can:

• Connect with external platforms
• Add new features easily
• Sync data in real time
• Expand system capabilities

APIs make web platforms flexible and ready for future growth. If a business wants to add new services or tools later, the system can support those changes without major rebuilding.

Business Impact and Client Benefits

The expanded web development services by the company are designed to deliver clear and measurable benefits for businesses across industries.

● Improved Scalability and Performance

Businesses benefit from web platforms that handle growth smoothly. Whether traffic increases or new features are added, the system remains stable and fast. This helps businesses avoid performance issues and costly rebuilds.

● Reduced Operational Complexity

Well-structured web systems reduce technical issues and simplify management. Businesses can focus on growth instead of constant maintenance. Clear system design also helps teams manage content, data, and integrations more easily.

● Faster Digital Transformation for Businesses

With modern tools and scalable design, businesses can adopt digital solutions faster. This supports quicker market entry, better customer engagement, and improved service delivery. JPLoft’s approach helps businesses move forward with confidence in their digital strategy.

Overall, clients gain reliable web platforms that support both current needs and future growth.

Industries and Business Types Served

JPLoft’s expanded web development services are designed to support a wide range of business types and industries.

► Startups, SMBs, and Enterprises

Startups benefit from flexible platforms that scale as their businesses grow. Small and medium businesses gain reliable systems that support expansion without high costs. Enterprises receive scalable solutions that manage large user bases, data volumes, and complex operations.

► Key Sectors Supported

JPLoft serves multiple industries, including technology, healthcare, education, retail, real estate, logistics, and professional services. Each solution is tailored to industry needs, ensuring compliance, usability, and performance.

By serving diverse sectors, JPLoft brings cross-industry experience that strengthens every project.

Commitment to Innovation and Long-Term Growth

JPLoft remains committed to continuous improvement and innovation. Alongside its full stack development services, the company invests in new technologies, team training, and refined processes to deliver stronger, measurable results. Every project is built with reliability, scalability, and long-term performance in mind.

The company understands that lasting digital success begins with solid technical foundations. Through quality engineering and strategic execution, JPLoft helps businesses build platforms that support steady growth and adapt to evolving market demands.

This approach ensures clients receive more than just a website — they gain a dependable digital asset built for sustained value and future expansion.

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TTEC Sets New Standard for AI-Driven Frontline Performance with TTEC Perform™ and TTEC RealSkill™

Globe Newswire

February 17, 2026

TTEC Sets New Standard for AI-Driven Frontline Performance with TTEC Perform™ and TTEC RealSkill™

Integrated AI training and performance ecosystem significantly improves associate proficiency, performance and sales across TTEC’s global contact centers

TTEC Holdings, Inc., a leading global CX (customer experience) technology and services innovator for AI-enhanced CX, announced the expansion and growing enterprise adoption of its AI-driven frontline performance ecosystem, anchored by TTEC RealSkill™ and TTEC Perform™.

Built to bridge the gap between AI investment and real business outcomes, the integrated ecosystem enables organizations to operationalize AI across the associate lifecycle—from onboarding and skill development to coaching and real-time performance execution.

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Today, the solution supports 100+ enterprise clients and at least 25,000 frontline agents globally, helping organizations translate skills, behaviors, and data into sustained performance improvement at scale. Clients across industries have achieved measurable gains, including:

12% improvement in associate retention
6–8% reduction in average handle time
100% compliance accuracy within 60 days
23% increase in Net Promoter Score
10% lift in sales conversion rates

Unlike fragmented AI deployments limited to training or coaching, TTEC’s unified approach connects learning directly to frontline execution. By combining immersive AI-powered practice, performance intelligence, and closed-loop coaching, enterprises gain consistent, measurable impact across complex, high-volume CX environments.

“AI doesn’t change performance on its own — people do,” said Julie Stone, Group Vice President and Chief Learning Officer at TTEC. “What’s been missing in the market is a way to turn AI insights into everyday behaviors that drive results. When associates can practice in realistic environments, receive timely coaching, and see how their actions connect to business outcomes, that’s when transformation becomes real and repeatable.”

At the core of the ecosystem, TTEC RealSkill™ delivers immersive, AI-powered simulations that let associates practice real-world customer interactions in a safe, repeatable environment. TTEC Perform™ extends that foundation into daily operations, delivering AI-driven coaching, performance analytics, and automated root-cause analysis tied directly to business outcomes.

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Together, the platforms apply a single, consistent skills and behavior framework from onboarding through ongoing performance optimization—eliminating silos between learning, coaching, and execution.

By tagging AI-powered simulations to the same skills used in live coaching, the ecosystem creates a continuous feedback loop between learning and on-the-job performance, giving leaders a unified, real-time view of frontline effectiveness.

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Infosys and Anthropic Announce Collaboration to Unlock AI Value across Complex, Regulated Industries

PRNewswire

February 17, 2026

Infosys and Anthropic Announce Collaboration to Unlock AI Value across Complex, Regulated Industries

Collaboration launches in telecommunications with dedicated Anthropic Center of Excellence, expanding across financial services, manufacturing, and software development
Infosys Topaz^™ and Anthropic’s Claude models, including Claude Code, combine to automate complex workflows, accelerate software delivery, and build agentic AI solutions across industries

Infosys, a global leader in next-generation digital services and consulting, announced a strategic collaboration with Anthropic, an AI safety and research company, to develop and deliver advanced enterprise AI solutions to companies across telecommunications, financial services, manufacturing, and software development. The collaboration will begin in telecommunications with a dedicated Anthropic Center of Excellence to build and deploy AI agents tailored to industry-specific operations. The collaboration will further expand across industries, including financial services, manufacturing, and software development.

At its core, the collaboration integrates Anthropic’s Claude models, including Claude Code, with Infosys Topaz AI offerings to help enterprises automate complex workflows, accelerate software delivery, and adopt AI with the governance and transparency that regulated industries require.

The collaboration reflects a shared commitment to ensuring AI drives real transformational value, not just efficiency gains. Together, Infosys and Anthropic aim to help clients reimagine the enterprise operating model by combining deep industry expertise, frontier AI, and engineering scale into one unified approach.

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A core focus will be agentic AI – systems that go beyond answering questions to independently handling multi-step tasks like processing claims, generating and testing code, or managing compliance reviews. Using tools like the Claude Agent SDK, Infosys and Anthropic will help clients build AI agents that can work persistently across long, complex processes rather than one-off interactions. The collaboration will also help organizations modernize legacy systems, combining Infosys Topaz and Claude to accelerate migration and reduce the cost of updating aging infrastructure.

Building on these agentic AI capabilities, Infosys and Anthropic will develop custom AI agents tailored to specific industries and business functions:

In telecommunications, AI agents will help carriers modernize network operations, streamline customer lifecycle management, and improve service delivery – bringing intelligent automation to one of the most operationally complex and heavily regulated industries in the world.
In financial services, AI agents will help firms detect and assess risk faster, automate compliance reporting, and deliver more personalized customer interactions – such as tailoring financial advice based on a client’s full account history and market conditions.
In manufacturing and engineering, Claude will help accelerate product design and simulation, reducing R&D timelines and enabling engineers to test more iterations before production.
In software development, teams will use Claude Code to write, test, and debug code – helping developers move faster from design through production. Infosys is already deploying Claude Code within its own Exponential Engineering organization, building internal expertise and best practices that will directly inform client engagements.

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Dario Amodei, Chief Executive Officer and Co-Founder, Anthropic, said, “There’s a big gap between an AI model that works in a demo and one that works in a regulated industry – and if you want to close that gap, you need domain expertise. Infosys has exactly that kind of expertise across important industries: telecom, financial services, and manufacturing. Their developers are already using Claude Code to accelerate their work and to create AI agents for industries that demand precision, compliance, and deep domain knowledge.”

Salil Parekh, Chief Executive Officer, Infosys, said, “AI is not just transforming business – it is redefining the way industries operate and innovate. Our collaboration with Anthropic marks a strategic leap toward advancing enterprise AI, enabling organizations to unlock value and become more intelligent, resilient, and responsible. From modernizing financial services with intelligent risk management and compliance, to enabling engineering businesses to lead with AI-driven design and manufacturing, the goal is to leverage the joint expertise of Infosys and Anthropic to accelerate AI value realization for global enterprises.”

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MarTech Interview With Misha Williams, Chief Operating Officer @ GWI

Paroma Sen

February 17, 2026

MarTech Interview With Misha Williams, Chief Operating Officer @ GWI

How can modern marketers optimize how they set up their AI powered martech stacks for better marketing output? Misha Williams, Chief Operating Officer at GWI weighs in with some thoughts and best practices:

_________

Hi Misha, tell us about yourself and your role at GWI?

I’m Chief Operating Officer at GWI, where I focus on scaling the business at the intersection of insights and AI. My role spans product, revenue, marketing, partnerships, and operations – but the common thread is impact. We’re building systems that help organizations move faster without losing sight of their customers. At its core, my job is making sure human truth actually shows up in everyday business decisions.

We’d love to hear more about GWI’s latest launch – Agent Spark, how does it benefit end users?

Agent Spark is built for a world where AI is the default interface for work. It brings trusted, analyst-grade human insights directly into tools like ChatGPT, Claude, and Copilot – no scraping or guesswork. For users, that means faster decisions that are grounded in real people, and what we describe as human truth, not averages or assumptions. It’s AI that knows people, not just patterns.

What should modern marketers keep in mind when deploying and setting up AI powered systems to analyze and support marketing workflows?

The biggest mistake is treating AI outputs as fact without interrogating the inputs. If your system isn’t grounded in real, representative human data, you’re just automating bias and noise at scale. Marketers that design AI workflows with transparency, provenance, and a clear human-in-the-loop model are setting themselves up to win – AI should accelerate judgment, not replace it.

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As AI powered tools become more mainstream in martech and marketing: how do you feel the scope of a marketing role will change down the line?

Marketers won’t disappear, but their work will shift dramatically. Execution gets automated; interpretation, strategy, and cultural judgment become the differentiators. The best marketers will act more like editors-in-chief of intelligent systems – guiding, challenging, and refining AI outputs using real audience understanding. Human insight becomes the competitive edge.

Five of the best AI powered martech features that most marketers haven’t fully unlocked the power of yet?

GWI unlocks the following for marketers:

AI agents are grounded in real human data, not synthetic personas.
Natural-language insight querying that replaces static dashboards.
Embedded insights directly inside creative, media, and planning tools.
Dynamic audience insight that updates as culture shifts.
Explainability, meaning AI that shows why an insight matters, not just what it found.

A few thoughts surrounding the future of martech before we wrap up?

Martech is moving from stacks to systems, and from tools to intelligence. The winners will be platforms that embed human understanding directly into workflows, products, and agents. As AI scales, relevance becomes scarcer, not easier. The future belongs to brands and platforms that build with human truth at their core, not as an afterthought.

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GWI, is the human insights company powering faster, smarter strategic decisions in an AI-driven world

About Misha Williams

Misha Williams is Chief Operating Officer at GWI, he leads GWI’s global operating model across product, revenue, marketing, partnerships, and business operations, translating the world’s most globally representative proprietary human dataset into scalable AI-powered insight systems embedded directly into modern decision-making.

AXIS Consulting Shares a Practical Model for Scaling AI, Automation, and CRM Change

MTS Staff Writer

February 17, 2026

Inogic Launches AI-Powered Solutions for Dynamics 365 CRM: Predictive Analytics, AI Document Search & Next Best Action

Framework helps leaders move beyond pilots to governed, repeatable outcomes across AI, automation, and CRM systems

AXIS Consulting introduced a practical operating model designed to help mid-market and enterprise organizations scale artificial intelligence, automation, and CRM change beyond isolated pilots. The model responds to a growing challenge leaders face: experimentation with AI is accelerating, but operational impact is not.

We design systems that get smarter and more valuable over time, so teams are not starting from zero every few months.”

— Boris Tsibelman, Founder & CEO of AXIS Consulting

As organizations modernize CRMs, deploy automation, and introduce generative AI, many initiatives stall when treated as technology installs rather than operating changes. AXIS Consulting’s model is designed to close that gap by aligning strategy, data readiness, workflow design, governance, and adoption into a repeatable delivery system, particularly in modular stacks where CRM, scheduling, proposals, automation, and telephony must operate as one coordinated whole.

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“This model is built for organizations that want AI and automation to compound, not reset every quarter,” said Boris Tsibelman, Founder & CEO of AXIS Consulting. “Scaling change requires discipline around prioritization, governance, and adoption not just new tools.”

A Five-Component Operating Model:

The model is organized around five connected components that can be implemented in phases. Together, they provide a practical structure for prioritizing initiatives, managing risk, and ensuring measurable improvement over time.

1. Use-Case Portfolio with Value Gates

The model begins with an intake process that evaluates proposed initiatives—such as AI assistants, lead-routing automations, or CRM workflow changes—against impact, feasibility, and risk. Each use case names an owner, defines baseline metrics, and documents a value hypothesis before work begins, helping teams avoid pilot sprawl.

2. Data, Security, and Governance Foundations

AI and automation amplify both good and bad data. The model establishes clear rules for access, quality controls, auditability, and shared definitions across systems. This foundation is critical in environments where CRMs paired with tools such as PandaDoc, Aircall, and Zapier feed the same executive dashboards.

3. Process-First Design and Reusable Automation Patterns

Rather than automating broken steps, the model emphasizes mapping end-to-end workflows and applying standard, reusable patterns such as lead routing, approvals, follow-ups, and cross-team handoffs. Documenting patterns once and applying them consistently reduces exceptions and rework as organizations scale.

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4. Embedded Change Management

CRM and automation programs often lose momentum when users experience frequent changes without clarity. The model embeds enablement, role-based rollouts, and ownership into delivery so adoption keeps pace with execution and avoids shadow processes.
5. Measurement and Continuous Improvement.

The final component focuses on tracking a short list of operational KPIs such as cycle time, conversion rates, response times, and forecast accuracy alongside adoption and data quality metrics. Systems are treated as operational instruments, with ongoing checks to ensure automations remain auditable, secure, and maintainable.

AXIS Consulting said the model is designed for executives and operators responsible for revenue operations, customer experience, IT, data, and transformation leadership. It supports initiatives including CRM modernization, workflow redesign, and governance for generative AI tools across modular software stacks.

The firm emphasized that the goal is not automation for its own sake, but durable operating improvement so AI-enabled change compounds quarter over quarter rather than stalling after launch.

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Starweaver Expands AI Engineering Presence in Hyderabad

MTS Staff Writer

February 17, 2026

Starweaver Expands AI Engineering Presence in Hyderabad

Starweaver announced the continued expansion of its AI engineering and product development operations in Hyderabad, India, reinforcing the company’s long-term commitment to building advanced AI-powered learning infrastructure.

The Hyderabad technology center will focus on accelerating development of Starweaver’s AI-driven platforms, including Journeybuilder (and its accompanying orchestration tools within Creator Studio and Enterprise Studio), DesignPilot, Boostr workflow integrations, Starweaver analytics intelligence systems, and adaptive learning tools for enterprise and institutional partners.

Over the next six months, Starweaver expects to grow its Hyderabad-based engineering and data teams by approximately four times their current size, adding high-skilled roles across AI research, applied machine learning, data engineering, product architecture, and scalable systems design.

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This expansion reflects increasing demand for AI-powered learning, content automation, and enterprise analytics across corporate training, professional development, and higher education markets worldwide.

“Our investment in Hyderabad is about focus and capability,” said Paul Siegel, Founder of Starweaver. “We are building a concentrated AI engineering environment where product teams can iterate quickly and responsibly. The next phase of growth for Starweaver is deeply rooted in artificial intelligence — not as a feature layer, but as core infrastructure.”

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The Hyderabad team works in close coordination with Starweaver’s global leadership and product teams to advance:

AI-assisted curriculum generation

Intelligent content orchestration and artifact management

Enterprise performance analytics

Adaptive, role-based learning journeys

Agentic AI integrations for workflow-based learning

“Hyderabad gives us access to exceptional AI and systems talent,” said Manas Dasgupta, Chief Technology Officer at Starweaver. “Our focus is on building scalable, production-grade AI systems that enterprises can deploy with confidence. This is not experimental innovation — it is operational AI.”

The expansion reinforces Starweaver’s broader strategy of unifying AI-powered learning design, content automation, analytics intelligence, and enterprise distribution within a single integrated ecosystem.

Rather than a traditional regional office opening, the Hyderabad centre represents a disciplined scaling of Starweaver’s core AI capabilities to support global partners and clients.

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Comcast Business Powers February’s Biggest Broadcast Events

Business Wire

February 17, 2026

Comcast Business Powers February’s Biggest Broadcast Events

Serving as the network backbone for NBCUniversal’s live broadcasts on the world’s biggest stages

Comcast Business announced it is again partnering with NBCUniversal to architect and manage critical components of the linear and digital broadcast for three of television’s marquee events this month – Super Bowl LX, the Milan Cortina 2026 Olympic Winter Games, and the 2026 NBA All-Star Game. With major productions occurring within days of each other, Comcast Business provides the end-to-end connectivity that underpins NBCUniversal’s live coverage across broadcast, cable, and streaming platforms.

“We’re proud to power the backbone of NBCUniversal’s live broadcasts on some of the world’s biggest stages this February,” said Ed Zimmermann, President, Comcast Business.

In advance of these broadcasts, Comcast Business connects NBCUniversal’s broadcast hubs, studios, and owned television stations through a dedicated fiber network that carries live video and data securely and reliably across NBCUniversal’s U.S. and international broadcast operations. This integrated network supports everything from delivering content to local NBC affiliate stations to powering live feeds for viewers – ensuring seamless coverage from opening moments to the final celebration. Using private, high-capacity connections that are continuously monitored and built with multiple network paths for redundancy, Comcast Business helps ensure NBCUniversal’s broadcasts stay on the air without interruption during television’s most-watched live moments.

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“Comcast Business has been an important and strategic partner in our planning and production of three of the biggest events on the sports calendar within the span of a week,” said Rick Cordella, President, NBC Sports. “With such a complex undertaking for our team, Comcast Business’ design and management of the infrastructure has given us full confidence that we can deliver a best-in-class presentation.”

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For the Winter Olympics, NBCUniversal is presenting more than 3,200 hours of coverage – including 2,500+ hours of streaming and every one of the 116 medal events live on Peacock. Comcast Business will power the live production network connecting NBCUniversal’s studios and venues in Italy with operations centers in the United States. This modern production approach enables remote and at‑home production capabilities, improving operational efficiency and resiliency while ensuring high picture quality for audiences watching around the globe.

“We’re proud to power the backbone of NBCUniversal’s live broadcasts on some of the world’s biggest stages this February,” said Ed Zimmermann, President, Comcast Business. “Our role is to design and manage the resilient, high-performance networks these moments demand – so producers can focus on storytelling, knowing the infrastructure behind every live feed is engineered, monitored, and ready when it matters most.”

This work represents another chapter in Comcast Business’s long-standing role supporting NBCUniversal’s most-watched live events, including prior Super Bowls and Olympic Games, and reflects the company’s continued investment in infrastructure designed for time-critical, large-scale events.

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Amtelco Releases Ellie™ an AI-powered Intelligent Virtual Agent

Business Wire

February 17, 2026

Former OpenAI & Google AI Experts Launch HyperDev

Ellie™ is powered by artificial intelligence (AI) and supports call centers by working with agents to better serve callers.

Amtelco announced the release of Ellie™ an intelligent virtual agent (IVA) platform capable of handling caller interactions with an automated, artificial intelligence (AI)-based agent that utilizes a large language model (LLM) and natural language processing (NLP). Ellie augments live agents when call centers experience overwhelming call volumes by offering automation and intelligently processing existing live agent call scripts to reduce caller wait times.

Together, Ellie and call center agents create an experience that offers unparalleled service.

Ellie is natively designed to run on Amtelco’s Intelligent Series (IS) version 6.0 software and its cloud-based LLM is hosted through the Active Insights platform. Ellie reduces the burdens experienced by agents by intelligently handling caller inquiries, providing real-time transcription, and offering an enhanced, cloud-based text-to-speech feature.

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The LLM interacts with a caller to have an intelligent conversation, and NLP enables Ellie to speak and understand speech like a human for a more life-like feel. Together, Ellie and call center agents create an experience that offers unparalleled service to callers while providing cost-savings and scalability to contact centers. Key features of Ellie include the following:

Advanced Applications – Utilize Ellie for automated directory assistance, appointment scheduling, automated code calls, prescription refills, and more.
Real-time Language Translation – Ellie can understand, translate, and respond to callers in their preferred language.
Automate Live Calls – Choose which calls to automatically direct to Ellie based on criteria, including call volume and wait times.
Transfer Live Calls to Ellie – Agents can pass callers to Ellie to complete the call, perform a survey, or handle other services.
Utilize Existing Live Agent Call Scripts – Ellie understands the entire script and can perform advanced scripting functions, including directory assistance, API interactions, and advanced dispatching.

“Ellie is based on our IS call center platform and leverages our IS scripting engine,” said Kevin Beale, Amtelco’s Vice President of Software and R&D. “One of the keys to Ellie is that it is part of our core IS platform. This fully integrated AI solution offers significant benefits such as flexible call routing, enhanced navigation menus, automated outbound calls, and automated analytics.”

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Ellie is the nickname of Eleanor Curtin, one of Amtelco’s co-founders and matriarch of the Curtin family who still owns and operates Amtelco. The name Ellie was purposefully chosen to honor the legacy of “Mrs. C” and to stress the importance of this product to Amtelco and its customers.

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Async Introduces an Agentic AI Framework for Audio and Video Production

MTS Staff Writer

February 16, 2026

Cannon Studio Develops Unified Platform for AI Video Creation and Workflow Management

Async, recently rebranded from Podcastle, today announced its first major platform update, introducing a fully agentic production workflow. The update lets creators bypass manual timelines and produce ready-to-publish content simply by chatting — cutting footage, shaping stories, adding voiceovers, and enhancing video and audio quality through natural language. The new chat-based workflow reduces post-production time for a standard one-hour recording from 20–48 hours to just minutes.

Creators are adopting generative AI rapidly, but the way content is produced has lagged behind. Adobe reports that 86% of creators are already using generative AI tools, yet much of the workflow remains manual, particularly the time-consuming process of reviewing raw footage and assembling usable moments. Async’s update responds to this shift by treating natural language as the primary interface for production, allowing creators to move from hands-on editing to high-level direction, while the system executes the work on their behalf.

For the engineering community, Async is opening the “black box” of its proprietary infrastructure through the Async Voice API, aiming to offer one of the best quality-to-cost ratios on the market. The API provides developers with direct access to the same low-latency voice production engine used across the Async platform, enabling the creation of real-time conversational agents, streaming tools, and live applications.

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“Our mission is to democratize video and audio production. You shouldn’t need a dozen different apps to bring one idea to life. We’re moving past tools and into systems that understand intent,” said Arto Yeritsyan, CEO and Founder of Async. “The manual editing job is disappearing. With this update, we’re making production invisible — connecting creative intent directly to execution. You don’t edit anymore; you direct.”

To support high-compute agentic workflows, Async is shifting to a hybrid pricing plan where regular subscriptions cover studio access while credits fuel AI generative features. This allows creators to scale their use of the platform features on demand, using monthly allowances or instant top-up packs. The Async Voice API operates on a flexible pay-as-you-go basis.

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The new agentic features and the Async Voice API are available via the Async web platform. Creators can produce ready-to-publish audio content starting today, with video capabilities coming later. New users can access a one-week free trial to experience the workflow.

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Rank Street Marketing Launches GEO Systems to Help Local Brands Win in AI Search

MTS Staff Writer

February 16, 2026

DTOM Soft Launch Breadth Edits AI Motion Engine for SaaS Promos

Rank Street Marketing Unveils AI-Driven Lead Generation Suite to Bridge the Gap Between Local SEO and Generative Chat

Rank Street Marketing, a leading digital growth agency specializing in high-performance marketing for local service industries, has officially announced the launch of its new Generative Engine Optimization (GEO) service suite. This new offering is specifically designed to help local businesses move beyond traditional search rankings and secure visibility within the AI-driven “answer engines” that are redefining how consumers find services in 2026.

As AI platforms like Google Gemini, ChatGPT, and Perplexity become primary tools for consumer research, the traditional goal of “Page 1” is no longer the final milestone. Rank Street Marketing’s new GEO system ensures that local brands are not just indexed by search engines, but are actively recommended and cited as authoritative answers within AI-generated responses.

CAPTURING LEADS IN THE ERA OF AI CHAT

The shift from standard search to conversational AI represents the biggest change in digital marketing in over a decade. Rank Street Marketing’s new framework addresses this by optimizing a business’s entire digital footprint—from Google Business Profiles to structured website data—to satisfy the complex retrieval-augmented generation (RAG) models used by modern AI.

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“The search bar is evolving into a conversation,” says a spokesperson for Rank Street Marketing. “If a homeowner asks an AI, ‘Who is the most reliable contractor near me?’, the business that wins is the one with the strongest authority signals across the web. Our GEO systems are built to ensure our clients are the first name mentioned by the AI, whether through organic citations or targeted AI-integrated ads.”

A MULTI-LAYERED APPROACH TO LOCAL AUTHORITY

The new Rank Street Marketing service suite includes:

GENERATIVE ENGINE OPTIMIZATION (GEO): A proprietary process to increase a brand’s “mention rate” and citation authority in AI-generated answers.

AI-TARGETED LEAD GENERATION: Specialized strategies for capturing leads directly from conversational result pages and AI search interfaces.

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LOCAL ENTITY STRENGTHENING: Enhancing NAP (Name, Address, Phone) consistency and third-party validation to build trust with Large Language Models (LLMs).

CONVERSION-CENTRIC DESIGN: Web platforms built to turn AI-referred traffic into high-intent leads within seconds.

Rank Street Marketing continues to offer its signature 90-day organic ranking guarantee, now bolstered by these AI-first strategies to provide a comprehensive competitive edge for local contractors, medical spas, and professional services.

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LatentView Analytics Appoints Kiran Muddana to Advisory Council to Strengthen Enterprise AI and Data Strategy

MTS Staff Writer

February 16, 2026

LatentView Analytics Appoints Kiran Muddana to Advisory Council to Strengthen Enterprise AI and Data Strategy

Former Google and Amazon leader brings two decades of experience driving large-scale data and AI transformation to support LatentView’s global growth

Latent View Analytics Limited (LatentView Analytics | BSE: 543398, NSE: LATENTVIEW), an AI-driven analytics, data engineering, and consulting firm, today announced the appointment of Kiran Muddana to its Advisory Council. Kiran brings more than 18 years of experience leading enterprise-scale AI, analytics, and technology transformation initiatives at global organizations including Google and Amazon.

Kiran brings deep experience in translating enterprise goals into scalable technology strategy,”

— Rajan Sethuraman, CEO, LatentView Analytics

In his advisory role, Kiran will work with LatentView’s leadership team to provide strategic input on client delivery, AI adoption, and data-led business transformation. His appointment supports LatentView’s focus on helping enterprises scale AI responsibly and deliver measurable business value through data.

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“Kiran brings deep experience in translating enterprise goals into scalable technology strategy,” said Rajan Sethuraman, CEO of LatentView Analytics. “He understands how to align data and AI investments with business outcomes and will be an important voice as we continue to grow and evolve our offerings.”

Throughout his career, Kiran has worked closely with senior leaders across HR, Sales, Marketing, and Finance to address complex business challenges. He has led programs that generated new revenue, improved product adoption, and reduced operational costs. His work focuses on practical implementation of AI and data strategies that are tied to clear business impact.

Commenting on the appointment, Kiran said, “I am grateful for this opportunity to join LatentView Analytics in an advisory capacity. Having partnered closely with the LatentView team at Google, I experienced firsthand the team’s ability to combine deep analytics expertise with strategic clarity and rapid execution to deliver meaningful business impact. I look forward to collaborating with the team to shape data and AI-led strategies that help organizations unlock long-term, sustainable value.”

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LatentView helps enterprises operationalize AI through a consolidated suite of solutions that address core functions such as marketing, supply chain, product innovation, and risk. These offerings are supported by a library of AI accelerators and implementation frameworks that help clients move from strategy to execution with greater speed and consistency.

Kiran will advise on strategic initiatives tied to client success and enterprise readiness for AI. He will also support LatentView’s efforts to strengthen its delivery capabilities and expand its footprint with global clients.

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Rockwell Automation Digital Twin Technology Accelerates Project Delivery and Cuts Costs for Brazil-based Falcare Industrial Equipment

PRNewswire

February 16, 2026

Rockwell Automation Digital Twin Technology Accelerates Project Delivery and Cuts Costs for Brazil-based Falcare Industrial Equipment

Rockwell Automation, the world’s leading company dedicated to industrial automation and digital transformation, is pleased to announce that it has achieved significant time savings, improved project accuracy and reduced operational costs for Falcare Industrial Equipment in Sao Caetano do Sup in Brazil.

With more than 50 years serving retail, wholesale, food and beverage, logistics operations and automotive and machinery sectors, Falcare sought to strengthen project reliability and reduce time-consuming physical testing. The company faced increasing pressure to shorten sales cycles, eliminate field implementation rework and enhance the precision of complex automation systems.

To address these challenges, Falcare turned to Rockwell Automation’s digital twin technology, utilizing Emulate3D™ to simulate mechanical behavior, including robot and conveyor speeds, before machines were ever built. This approach significantly improved sustainability, energy efficiency and operational predictability.

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By integrating Rockwell Automation’s suite of digital simulation and virtual commissioning tools, Falcare achieved:

60% faster project execution, enabling quicker customer previews and accelerated delivery timelines.
Greater precision and quality, thanks to early validation that mitigates failures, errors and costly rework.
Improved decision-making, driven by accurate digital modeling of equipment behavior.
Reduced waste and energy use, resulting in more sustainable operations.

This project represents a truly innovative leap forward as few Brazilian companies currently use virtual commissioning with control logic emulation to enhance post-sales support and cut implementation costs. Before adopting Rockwell’s technologies. Falcare attempted alternative tools but encountered limitations, including restricted modeling capacity, inadequate mechanical–automation integration and data–processing bottlenecks. Emulate3D™ solved these issues by providing seamless integration between mechanics and controls, delivering a dynamic, highly accurate digital representation of the entire system. This enabled Falcare to preview system behavior, validate control logic and identify physical discrepancies well before deployment, reducing uncertainty and streamlining commissioning.

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Falcare and Rockwell Automation set a new standard for intralogistics engineering. By replacing traditional prototype testing with immersive digital simulation, Falcare can now:

Confidently demonstrate system performance to customers early in the sales cycle.
Enhance post–sales support with greater visibility into system behavior.
Deliver faster, greener, and more reliable automation solutions.

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Website Engagement Increased by Over 120% Following Digital Marketing and Website Redesign Initiative by Digital Silk

PRNewswire

February 16, 2026

Website Engagement Increased by Over 120% Following Digital Marketing and Website Redesign Initiative by Digital Silk

Digital Silk, an award-winning agency focused on creating brand strategies, custom websites, and digital marketing campaigns, has released a new case study highlighting measurable engagement gains following a digital marketing and website redesign initiative for Picture Perfect Cleaning. The project demonstrates how improved site structure, SEO, and user pathways can support stronger performance for service-based businesses operating in competitive local markets.

The Case Study outlines Digital Silk’s work with Picture Perfect Cleaning, a professional residential and commercial cleaning company seeking to improve online visibility and user engagement following the launch of a redesigned website in July 2025. The engagement focused on strengthening SEO foundations, improving navigation, and aligning digital marketing efforts with clearer conversion pathways.

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Improving Discoverability and Engagement Through Digital Marketing

Picture Perfect Cleaning required a digital presence that could support increased search visibility while keeping users engaged once they arrived on the site. Digital Silk’s approach centered on SEO optimization, streamlined navigation, and user-focused page structure designed to guide visitors efficiently through key service information.

The redesigned website was supported by digital marketing strategies aimed at improving discoverability and encouraging longer, more meaningful site interactions.

Measured Performance Outcomes Identified in the Case Study

According to performance data referenced in the case study, the redesigned website and supporting digital marketing efforts were associated with the following outcomes:

Website sessions increased by 47.44%, driven by stronger SEO performance and improved navigation.
Engaged sessions increased by 71.22%, with engagement times reported as three times higher than direct traffic.
Average engagement time increased by 124.73%, indicating that clearer pathways helped keep users engaged for longer periods.

These metrics highlight how strategic digital marketing and website optimization efforts may influence both traffic quality and user behavior.

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Why Engagement Metrics Matter for Service-Based Businesses

For local and service-driven organizations, attracting traffic is only part of the challenge. Websites must also support clarity, usability, and intent-driven navigation to keep users engaged. The Picture Perfect Cleaning case study illustrates how aligning digital marketing strategy with website structure can support improved engagement outcomes following a site launch.

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Halper AI Announces Expansion to Latin America and Europe with Its AI Business Assistant for Solopreneurs and SMEs

Globe Newswire

February 16, 2026

MoversTech Releases Its Most Significant Platform Update of Recent Months

Halper AI announced its expansion into Latin America and Europe, introducing its AI Business Assistant for solopreneurs and small and medium-sized enterprises (SMEs). Founded by Eduard Gevorkyan, the company continues to expand its international presence by bringing automated communication, scheduling, CRM, and invoicing capabilities to new regional markets.

Halper AI is an AI-powered Business Manager designed for solopreneurs and SMEs in the beauty, wellness, fitness, and real estate sectors. The platform manages customer communications across WhatsApp, Instagram, and Telegram while automating scheduling, CRM, invoicing, and other operational processes.

As part of its expansion strategy, Halper AI is leveraging its proprietary product prioritization framework, KANDICE, to accelerate development and ensure efficient feature deployment across Latin America and Europe.

The Architect of Automation: Eduard Gevorkyan
To understand Halper AI’s dominance, one must look at its founder. Eduard Gevorkyan’s career is a masterclass in scaling systems, from learning organizational optimization at McKinsey & Company to mastering Strategy and Operations at Google. After exploring decentralized trust at OKX, he launched SoulsHub in 2023.

SoulsHub allowed users to interact with AI-powered licensed replicas of mentors, professional athletes, and coaches, a project that was acquired by a Saudi Arabian technology group for an 8 million $ in late 2024. Now, Gevorkyan is applying that same emotional and operational intelligence to the backbone of the global economy: the small business owner.

Why Halper AI is Dominating the SME Market
Unlike traditional CRMs or chatbots that demand constant attention, Halper AI acts as an invisible operator. It integrates with the tools business owners already use—WhatsApp, Instagram, Telegram, and digital calendars—to handle the “busy work” of running a business:

Automated Bookings: Managing schedules without back-and-forth messaging on WA, TG and IG.
Seamless Invoicing: Sending and tracking payments automatically.
Proactive Follow-ups: Ensuring no lead or client is forgotten.

The philosophy is radical: “Don’t open Halper”. While other apps compete for clicks, Halper measures success through “freedom metrics”—peace of mind, profit, and time spent away from screens. This approach has made it the go-to tool for service professionals like barbers, therapists, and real estate agents who want to focus on their craft rather than their phones.

Global Dominance and Strategic Partnerships

Halper AI isn’t just a promising startup; it’s a verified powerhouse that saves, on average, 35 hours per month for each Solopreneur or SME.

Its trajectory is marked by elite recognition and a rapidly growing footprint:

AWS Startup Leader: Ranked 4th among AWS startups, trailing only behind giants like Perplexity.
Unicorns Club: Recently crowned the winner of the Weekly Startup on the Unicorns Club and TOP 3 startups worldwide.
Strategic Ecosystem: An official Meta Business Partner, with additional support through the Nvidia Inception program and grants from Google.

The Secret Sauce: The KANDICE Framework
As Halper AI prepares for aggressive regional expansion, the speed and accuracy of their development are fueled by Gevorkyan’s proprietary prioritization framework: KANDICE.

Gevorkyan noticed that existing models like ICE or RICE often failed to distinguish between “cool” features and “critical” ones. A “must-have” bug fix might get the same score as a flashy new feature that users don’t actually need. To solve this, he combined ICE scoring (Impact, Confidence, Ease) with Kano categories.

Caliber Releases Inaugural Stakeholder Intelligence Report

Business Wire

February 16, 2026

Caliber Releases Inaugural Stakeholder Intelligence Report

Caliber, a stakeholder intelligence platform helping organizations build and protect trust, released its inaugural Stakeholder Intelligence Report, revealing global trends in brand, reputation, and data-driven communications. As economic anxiety, AI disruption, and geopolitical uncertainty intensify, leaders across industries are making higher-stakes decisions under conditions of compressed trust and heightened reputational risk. This report equips executives with data and actionable insights to support decision-making in 2026 and beyond.

The 2026 Caliber Stakeholder Intelligence Report draws on nearly one million responses from more than 360,000 individuals across 37 countries, surveyed between January 1 and October 31, 2025. Central to the report is Caliber’s parallel assessment of brand and reputation, an approach that distinguishes Caliber’s platform from other players in the traditional corporate reputation management space that tend to keep brand and reputation in discrete silos.

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Key elements of the report include:

Taking the temperature of stakeholder sentiment to establish the context within which people make decisions about companies
- Globally, the top three issues that most concern stakeholders are increased cost of living (36%), artificial intelligence (24%), and economic recession (20%), closely followed by unemployment (19%), rising energy prices (19%), and Donald Trump’s presidency (18%).
- Global financial optimism is down, with only three out of 37 countries (Denmark, Sweden, and the Netherlands) showing net-positive sentiment on how secure people feel in their future financial situation from 2024 to 2025.

Revealing the reputation of 14 industries in 2025 and how they have changed to uncover which stakeholder segments are losing trust in certain sectors, and which aspects of brand and reputation drive overall standing
- The most globally trusted and liked sectors are Fast-Moving Consumer Goods, MedTech, Retail, and Electronics & Appliances, all with Trust & Like Scores (TLS) of 72. The least trusted and liked sectors are Automotive and Telecom, both with a TLS of 65.
- The sectors with the largest declines in TLS are Big Tech and Automotive, which are down three and two points respectively from their 2024 scores.
Exploring the impact of awareness and familiarity on reputation to give marketing and communications teams actionable, data-backed insights to strengthen reputation in 2026
- Familiarity functions as a reputational buffer in periods of volatility. The more a company can tell its story and shift people from simply being aware of it to having qualified knowledge about it, the more insulated its reputation becomes from shocks—and the more resilient it is likely to be when crises emerge.
Analyzing employer attractiveness in the war for talent to equip CEOs and HR executives with the data-backed information they need to pull ahead in the AI talent race
- In 2026, employer attractiveness is no longer a soft metric—it is a gating factor for access to AI and engineering capability. The sectors that appeal most to job seekers are MedTech, Banking, Big Tech, and Chemicals, whereas Oil & Gas, Electricity, Telecom, and Automotive appeal the least, raising long-term competitiveness concerns for industries struggling to attract skilled talent.
- Among STEM talent specifically, this trend is similar, with the most appealing sectors being MedTech, Big Tech, and Chemicals, and the least appealing sectors being Telecom, Oil & Gas, Retail, and Automotive.

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“As the gap in stakeholder trust in corporations widens, the companies that will thrive are actively building brands that resonate and inspire instead of managing reputation reactively,” said Caliber CEO Shahar Silbershatz. “With our first annual Stakeholder Intelligence Report, we are putting Caliber’s real-time, multi-stakeholder, AI-augmented data and insights to work to help leaders make confident decisions under pressure, at a time when every choice carries reputational risk.”

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Peec AI Ranked Top Enterprise Platform for AI Search Visibility in 2026

MTS Staff Writer

February 16, 2026

Peec AI Ranked #1 Enterprise Platform for AI Search Visibility Tracking 2026 #AISearch #GEO #EnterpriseAI

A comprehensive new evaluation of AI search visibility platforms places Peec AI as the leading enterprise solution for tracking brand performance across major AI systems in 2026. The independent review, published in BusinessCloud, assessed 14 platforms based on multi-LLM coverage, citation analysis, sentiment tracking, and enterprise reporting capabilities.

The study reveals that 58% of searches in the US now generate AI-driven answers, fundamentally changing how brands must measure digital visibility. Traditional SEO rankings no longer capture whether and how AI platforms like ChatGPT, Gemini, Google AI Overviews, and Perplexity present brand information to users. This shift creates an urgent need for specialized tracking tools built specifically for AI-generated search environments.

A team of enterprise technology experts evaluated each platform using a structured framework reflecting the needs of large organizations tracking AI search visibility. Assessment criteria included prompt scale capacity for handling large daily prompt libraries, LLM coverage across major models, citation and sentiment analysis capabilities, reporting and integration features, pricing transparency, and verified user feedback from G2, Capterra, and LinkedIn discussions.

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The top 14 enterprise platforms for AI search visibility tracking in 2026 are:

1. Peec AI – best for multi-LLM visibility tracking
2. AIclicks.io – best for competitive benchmarking
3. Search Atlas – best for sentiment filtering
4. Gauge – best for share-of-voice metrics
5. Mint (GetMint) – best for content recommendations
6. Rankscale AI – best for detailed prompt-level metrics
7. Scrunch AI – best for optimization layer for content
8. LLMonitor – best for performance tracking
9. Semrush AI Visibility Toolkit – best for SEO integration
10. Finseo.ai – best for integrated SEO audits
11. OtterlyAI – best for custom prompt libraries
12. seoClarity – best for SEO workflow integration
13. BrightEdge – best for correlating visibility with traffic
14. LLM Pulse – best for share-of-voice metrics

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Peec AI distinguished itself as the strongest enterprise platform through comprehensive tracking capabilities across ChatGPT, Gemini, Perplexity, Claude, Google AI Overviews, Microsoft Copilot, DeepSeek, Grok, and Llama. The platform delivers prompt-level mention frequency, sentiment analysis, and position data at scale, with support for multi-country monitoring and enterprise-grade reporting.

Key enterprise features that positioned Peec AI at the top include classification of citation source types (editorial, UGC, competitor, reference, informational) to diagnose visibility origins, export-ready workflows with CSV output for downstream analysis, regex-based detection and prompt clustering for deep monitoring regimes, unlimited user seats eliminating per-user licensing costs, and daily monitoring with competitive benchmarking and trend tracking. These capabilities enable enterprise teams to understand which prompts perform best, which sources influence AI responses, and how brand perception shifts across models and regions.

Other evaluated platforms demonstrated specialized strengths. AIclicks.io combines visibility metrics with a content generation engine for closing gaps. Search Atlas integrates AI visibility with broader SEO workflows through sentiment filters and topic clustering. Gauge uses synthetic prompts for competitive benchmarking. Enterprise solutions like BrightEdge and seoClarity link AI visibility data with traditional SEO metrics and content performance indicators.

The research emphasizes that AI visibility represents a measurable search channel requiring dedicated tooling. AI-generated answers now influence brand discovery at massive scale, with platforms like Gemini embedded directly inside Google Search. Enterprise teams can no longer rely on traditional rank tracking to understand brand exposure, as visibility now depends on mention frequency, context quality, sentiment tone, and citation patterns rather than position in search results.

The evaluation framework prioritized capabilities essential for enterprise deployment. Prompt scale capacity ensures platforms handle large monitoring regimes without performance degradation. Multi-LLM coverage provides comprehensive visibility across the AI search landscape rather than single-model blind spots. Citation and sentiment analysis reveals not just whether brands appear but how AI systems frame and position them. Export and integration features enable teams to incorporate AI visibility data into existing workflows and reporting systems.

According to the research findings, enterprises selecting AI search visibility tools should prioritize multi-LLM coverage, sentiment and citation tracking, prompt-level visibility metrics, data export capabilities for analysis, integration with existing SEO workflows, scalability for large teams, and transparent pricing structures. These tools provide critical insights into how AI platforms present brands, enabling optimization of content for AI-driven search results and measurement of visibility across multiple models.

The study concludes that tracking AI search visibility has become essential for enterprises in 2026, as AI-generated search results increasingly influence brand exposure and customer discovery. Peec AI stands out as the strongest platform for comprehensive visibility tracking across major AI models, making it the top choice for enterprises requiring multi-LLM coverage, global tracking capabilities, and enterprise-ready reporting infrastructure.

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The Launch of Mefesio Messaging App, Ended the Long-Awaited Arrival, for an Easy-To-Use Decentralized Messaging App.

MTS Staff Writer

February 16, 2026

The Launch of Mefesio Messaging App, Ended the Long-Awaited Arrival, for an Easy-To-Use Decentralized Messaging App.

Mefesio marks the dawn of the of advanced decentralized messaging.

Over the years we have seen significant progress in messaging security with the adding of end-to-end encryption, but one thing remains missing is complete privacy. Despite all end-to-end encryption, these messaging apps are still run and stored by central servers.

In spite of offering end to end encryption, these apps still continue to collect meta data, therefore although it could be considered secure, it continues to lack the real definition of full privacy.

The data security company Defesio LLC,
introduces to the world the first encrypted SMS messaging app Tefesio,
which now also launches the first easy-to-use decentralized messaging App Mefesio.

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Unlike traditional messaging apps, Mefesio isn’t stored or controlled by central servers, therefore it’s more resistant to everyday breaches.

And due to its decentralized structure, Mefesio does not collect any metadata, which includes no phone numbers, IP addresses, locations, or any user activity.
Mefesio also does not require any phone number for registrations.

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One of the most unique features of this application,
Is also its ability to block profanity words and dangerous links, making it the first family and kids friendly encrypted messaging application worldwide.

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Why Media Mix Modeling So Rarely Works for B2B

Michael Kaminsky

February 16, 2026

Why Media Mix Modeling So Rarely Works for B2B

Consumer brands like P&G and Unilever have used media mix modeling (MMM) for decades to steer billions in spend. It’s natural for business-to-business (B2B) marketers to want the same tools. Yet when B2B teams roll out MMM, they often find unusably wide uncertainty intervals, volatile recommendations after each refresh, and weak forecast accuracy.

Why? The root cause isn’t poor implementation. It’s simply that B2B operates under different statistical conditions than business-to-consumer (B2C) brands.

Where MMM Works Well

MMMs are econometric tools that use historical patterns to estimate the causal impact of marketing on key business outcomes like revenue, leads, or new customers. They perform best when four conditions hold:

High transaction volume

provides statistical power. With thousands of daily orders, the model can learn from fine-grained variation.

Consistent offers and values

keep metrics stable. If most purchases fall in a predictable range (say $200–$800), averages like CPA and ROAS are meaningful. Extreme values make average measures less useful.

Short purchase cycles

tighten the link between ad exposure and conversion. Direct-response behaviors make cause and effect clearer.

Direct purchase paths

make causality clearer. Each additional step between ad exposure and an ultimate conversion introduces confounders that complicate measurement.

These conditions are common in CPG, ecommerce, and similar environments. A B2C sunglasses brand, for example, may have thousands of weekly orders, basket sizes averaging $150, decisions within days, and no sales team.

Why MMM Struggles in B2B

B2B tends to introduce properties that are challenging for econometric models:

Low volume.

An enterprise software firm might close ten deals per quarter. With sparse data, distinguishing real signal from noise is hard.

Extreme value variation.

Deal sizes can span orders of magnitude. If one contract represents 40% of the quarter’s revenue, “average” metrics have little use.

Long cycles.

Twelve to twenty-four months from awareness to signature blurs the tie between any specific marketing activity and the eventual close.

Complex buying processes.

Multiple stakeholders, procurement, technical evaluations, and legal issues inject variation unrelated to marketing.

These aren’t mere technical hurdles. They’re mathematical limitations. If you combine sparse data, high variance, long lags, and complex conversion paths, traditional models will struggle to find reliable patterns. The same approach that confidently measures a CPG campaign can become unreliable in enterprise B2B. No amount of sophistication can conjure signal from insufficient data.

Additional Complications

Sales variability.

After marketing hands off a lead, outcomes depend heavily on sales reps. Top performers might close 5× more than the median, so salesperson quality can be much more important than marketing effects.

Account complexity.

The person most influenced by marketing may not be the decision-maker. Wins and losses can reflect internal politics or product fit rather than media.

Where MMM Can Work in B2B

B2B isn’t monolithic. MMM can be viable where B2B resembles B2C:

Product-led growth or high-volume SMB.

Payments or SaaS serving thousands of small customers can generate enough frequency.

Self-service SaaS.

Monthly subscriptions without sales involvement create repeatable purchase events.

SMB-focused contracts.

$1k–$10k ACVs with shorter cycles provide statistical power.

Hybrid models.

Use MMM for the self-serve segment, but employ different methods (e.g., account analytics) for enterprise.

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The Validation Imperative

A critical point with any media mix modeling project is that if you can’t validate the model, you’re making million-dollar bets on assumptions. Yet common validation methods are likewise tougher in B2B:

Holdout forecasting.

Train on history and predict the future. With 18-month cycles, you might wait years to judge accuracy. By then the market may change.

Incrementality tests.

Geo-lift or controlled experiments offer ground truth, but low deal counts make effects hard to detect without very long tests.

Forecast tracking.

Comparing predicted vs. actual outcomes creates a feedback loop, but long cycles slow learning to a crawl.

Unless you can validate a model, you shouldn’t use it for decision-making. The temptation is to fill gaps with assumptions (uniform close rates, constant rep quality, tidy decay curves). Each may seem harmless. Added up, though, they can produce outputs that are way off the mark and precision without accuracy is worse than acknowledged uncertainty.

Navigating the Trade-offs

No method is perfect. There are trade-offs among precision, accuracy, timeliness, and cost. If you opt to pursue MMM in B2B:

Document every assumption, and share it.
Present uncertainty ranges honestly, even when they’re wide.
Set realistic expectations about what your model can and cannot estimate.
Align internally on limitations before Many firms discover too late that their results were too uncertain to drive decisions.

Also consider alternatives that are better suited to enterprise sales:

Account-level analysis and cohort views for complex deals.
Channel-specific experiments where volume allows.
Mix models for self-serve only, paired with relationship mapping and qualitative signals for enterprise.
Attribution hybrids (lightweight rules & experiments) to inform near-term optimization while acknowledging long-cycle uncertainty.

The B2B teams that succeed at measurement don’t force inappropriate tools onto their realities. They assess context honestly, pick methods that match, and validate ruthlessly. They know B2B is not B2C, and that admitting what you simply cannot know is the first step to discovering what you can.

Before adopting any method, MMM or otherwise, ask:

Do we generate enough data for this approach?
Can we validate outputs in a reasonable timeframe?
Are we relying on assumptions that paper over fundamental limitations?

If you can’t answer Yes, Yes, and No, you’re better off choosing another measurement approach.

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Provenir Launches Comprehensive Decision Intelligence Platform with New Agentic AI Features to Supercharge Business Performance and Agility

Business Wire

February 16, 2026

Provenir Launches Comprehensive Decision Intelligence Platform with New Agentic AI Features to Supercharge Business Performance and Agility

Organizations can now compress strategy testing from months to days, enabling true hyper-personalization, leveraging AI that fits within stringent regulatory and governance frameworks

Provenir, a global leader in AI risk decisioning, announced the launch of its comprehensive decision intelligence platform with new agentic AI features to supercharge business performance and operational agility.

Provenir’s Decision Intelligence platform brings together data, models, decisioning, and optimization in one continuous system. With the platform, organizations can transform raw customer data into rich, insight-driven “signals” that reveal behaviors, risks, and preferences, enabling financial institutions to make smarter, more personalized decisions in real-time.

The platform also offers new capabilities for best-in-class model management to monitor and improve machine learning models. Users also gain robust simulation capabilities that reduce the time required for strategy testing from months to weeks and days, giving organizations the agility and confidence to proceed with the best approach, aligned with economic, regulatory, and business shifts.

This unified platform ensures decisions are executed, measured, learned from, and improved upon — without fragmentation across tools or teams. By connecting decisions to outcomes and recommending what to change for improvement, the platform enables organizations to confidently align decisioning to achieve business goals, make smarter risk/reward trade-offs, and shift swiftly as needed.

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A new AI assistant is embedded within the platform, providing familiar Natural Language access to information with ease. This enables users to interrogate and understand their data as well as harness the technology to complete specific tasks such as automated document review.

Provenir helps aid the adoption of AI with a “human in the loop” oversight approach, providing the necessary transparency and explainability to provide an understanding of how and why AI makes decisions, to adhere to regulatory requirements and governance guardrails.

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“AI-enabled decisioning has shifted from differentiator to necessity. Intensifying competition, M&A activity, and rising customer expectations are putting pressure on institutions to move faster, personalize interactions, and manage risk with greater precision,” said Provenir’s Senior Vice President of Product Management David Mirfield.

“By delivering better decisions through a single Decision Intelligence platform, Provenir helps enterprises achieve accelerated digital transformation, operationalizing AI at scale. This transforms data into unified intelligence to drive improved agility, compliance and competitive advantage. With smarter, more consistent decisions comes improved profitability and customer growth.”

Additionally, Provenir is evolving its Global Data Marketplace into a unified hub for both data and AI by integrating leading public and private LLMs. Financial institutions can now access providers such as OpenAI and Anthropic through pre-integrated APIs, or use private, restricted instances hosted via AWS Bedrock to keep sensitive data fully protected. This gives customers a governed, plug-and-play way to embed powerful LLM capabilities directly into their decisioning, agentic workflows, and decision intelligence experiences, all within the Provenir platform.

Provenir’s unified platform approach powers decision intelligence across a wide variety of use cases. The solution supports both real-time and batch processing and can serve a broad array of industries, and various user roles within risk and credit departments, while scaling to support businesses of all sizes from small lenders to large financial institutions.

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How can modern marketers optimize how they set up their AI powered martech stacks for better marketing output? Misha Williams, Chief Operating Officer at GWI weighs in with some thoughts and best practices:

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Hi Misha, tell us about yourself and your role at GWI?

We’d love to hear more about GWI’s latest launch – Agent Spark, how does it benefit end users?

What should modern marketers keep in mind when deploying and setting up AI powered systems to analyze and support marketing workflows?

As AI powered tools become more mainstream in martech and marketing: how do you feel the scope of a marketing role will change down the line?

Five of the best AI powered martech features that most marketers haven’t fully unlocked the power of yet?

A few thoughts surrounding the future of martech before we wrap up?

Framework helps leaders move beyond pilots to governed, repeatable outcomes across AI, automation, and CRM systems

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Where MMM Works Well

High transaction volume

Consistent offers and values

Short purchase cycles

Direct purchase paths

Why MMM Struggles in B2B

Low volume.

Extreme value variation.

Long cycles.

Complex buying processes.

Additional Complications

Sales variability.

Account complexity.

Where MMM Can Work in B2B

Product-led growth or high-volume SMB.

Self-service SaaS.

SMB-focused contracts.

Hybrid models.

The Validation Imperative

Holdout forecasting.

Incrementality tests.

Forecast tracking.

Navigating the Trade-offs

Before adopting any method, MMM or otherwise, ask:

Organizations can now compress strategy testing from months to days, enabling true hyper-personalization, leveraging AI that fits within stringent regulatory and governance frameworks

Write in to psen@itechseries.com to learn more about our exclusive editorial packages and programs.

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Infosys Topaz^™ and Anthropic’s Claude models, including Claude Code, combine to automate complex workflows, accelerate software delivery, and build agentic AI solutions across industries