The help desk is finally getting a voice upgrade. Astreya Partners, a global IT managed services provider (MSP) serving some of the world’s biggest tech companies—including six of the so-called Magnificent Seven—has chosen 3CLogic to power its ServiceNow-based contact center with AI-driven voice technology.

The move reflects a growing trend in IT services: ditching email-heavy workflows in favor of conversational, real-time support that actually matches the urgency of enterprise IT issues. With more than 2,400 IT professionals spread across 40+ countries, Astreya needed a solution that could modernize interactions while squeezing more efficiency from its sprawling service operations.

Why Voice AI Now?

Email still dominates enterprise IT support—but it’s often the slowest way to solve complex problems. By bringing in 3CLogic’s Voice AI and omnichannel contact center platform, Astreya aims to deliver faster resolutions and create a unified workspace for agents, administrators, and clients.

Key features of the integration include:

• Omnichannel platform: A single workspace that combines voice with ServiceNow’s digital channels, cutting down on “swivel-chairing” between systems.

• Voice AI & automation: Conversational voicebots powered by ServiceNow data handle common requests while escalating complex cases to human agents.

• Real-time transcription & AI summaries: Calls are automatically transcribed and condensed into generative AI-powered notes, saving agents time and reducing errors.

• AI-powered coaching & QA: Speech analytics and performance monitoring let IT teams train and optimize at scale without manually reviewing every call.

A Smarter Service Desk

Romil Bahl, Astreya’s CEO, called the partnership a way to “deliver digital workplace services that scale, adapt, and continually raise the bar for service excellence.” His COO, Jothiganesh Nagarajan, added that the collaboration will bring “intelligent self-service, conversational AI, and sentiment analytics” to the company’s service desks—positioning Astreya as a leader in AI-driven IT support.

3CLogic, for its part, sees the ServiceNow tie-in as a natural fit. “IT departments are the backbone of any modern organization,” said Bob Doherty, VP of Sales at 3CLogic. “Embedding this functionality into existing ServiceNow workflows to drive exponential ROI is a no-brainer.”

What’s Next

The rollout starts with Astreya’s Digital Workplace Services division but won’t stop there. The MSP plans to extend 3CLogic’s capabilities across more business units, betting that AI-powered service desks will not just reduce costs but also improve client satisfaction—a critical differentiator in the competitive managed services market.

With IT service desks under pressure to deliver faster, leaner, and smarter support, Astreya’s playbook may become the template for other global MSPs looking to marry ServiceNow’s ITSM backbone with AI-driven voice automation.

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Cadent, the predictive advertising company, has wrapped its annual Upfront with a 26% year-over-year surge, signaling that advertisers are increasingly betting on predictive intelligence to navigate a fractured video landscape. The company’s pitch—unifying audiences across linear and digital while delivering digital-style accountability—appears to be resonating in a market that’s demanding both scale and measurable outcomes.

Predictive Advertising Gets Its Moment

At the core of Cadent’s growth is its Predictive Intelligence engine, honed over 15 years and powered by more than 22,000 custom machine learning models. Instead of waiting until after impressions are bought to optimize, Cadent scores them in advance, continuously adjusting campaigns in real time. The result: video can now be transacted and measured with the precision of digital, while still benefiting from the reach and certainty of traditional Upfront deals.

The 2025 Upfront cycle brought 22 new advertisers into Cadent’s fold, alongside a 12% boost in linear commitments—outpacing the broader TV marketplace, which continues to wrestle with declining viewership and splintered audiences.

“Advertisers are saying it loud and clear—they want more flexibility, proof of performance, and ways to bring digital accountability to all media,” said Doug Rozen, President of Cadent. “Our Upfront results demonstrate the market’s confidence in our ability to deliver any audience across a fully optimized media supply path.”

Convergence Is the New Battleground

The ad industry has been steadily moving toward converged media—where linear TV and digital channels are planned and measured in one system. Cadent’s growth underscores just how central that convergence has become. In the first half of 2025 alone, Cadent saw nearly 50% growth in digital campaigns and a whopping 137% increase in connected TV (CTV) spend, as advertisers reallocate budgets toward formats that bridge TV-style storytelling with digital accountability.

Cadent’s reach is bolstered by partnerships with more than 200 publishers, enabling advertisers to activate campaigns across premium inventory with the same predictive modeling used in digital performance channels. Today, over 1,500 advertisers and agencies lean on Cadent’s platform—including 70+ self-service agencies representing 850+ brands.

Why It Matters

The results reflect a broader shift in advertiser expectations. Economic uncertainty, fragmented audiences, and mounting pressure for ROI have forced marketers to demand more than just reach. The big win for Cadent is positioning itself as both a bridge and a filter: unifying audiences across channels while ensuring every impression is scored for its potential to drive outcomes.

For rivals in the converged TV space—from The Trade Desk to Comcast’s FreeWheel—the takeaway is clear: advertisers don’t just want scale, they want predictive precision. And Cadent’s Upfront haul shows that if you can offer both, the budgets will follow.

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Workato, best known for its low-code automation platform, is making a bold play for the future of enterprise AI. Today, the company unveiled Workato Enterprise Model Context Protocol (MCP), which it claims is the most complete and secure way to connect large language model (LLM) agents—think ChatGPT, Claude, Amazon Q, and Google Gemini—with the messy reality of enterprise applications and workflows.

It’s a move aimed squarely at solving one of the biggest headaches in AI adoption: how to let AI agents take real action with real data, without opening a Pandora’s box of security risks or unreliable automation.

Why MCP Matters Now

For the past year, enterprises have been experimenting with AI copilots and chatbots, hoping to translate hype into productivity. The problem? Open-source MCP servers—essentially middleware for AI agents—are everywhere, but most lack the enterprise-grade security, identity management, and governance that IT leaders demand.

“MCP has shown great promise, but hasn’t delivered when it comes to seeing value with core business processes,” said Adam Seligman, CTO of Workato. “Workato Enterprise MCP changes that by bringing the full spectrum of business processes, from the front office to the back office and everything in between, to AI agents through MCP.”

The stakes are high. Analysts predict MCP could become the de facto standard for how AI agents talk to enterprise apps. But without guardrails, those same agents risk turning into compliance nightmares or worse—unreliable assistants that break workflows instead of accelerating them.

Workato’s Pitch: Secure, Managed, Enterprise-Grade

Workato is positioning its Enterprise MCP as the antidote to “DIY disasters.” Instead of running open-source servers full of untrusted code, enterprises can use Workato’s fully managed, serverless MCP servers that come pre-loaded with governance, observability, and enterprise-grade security.

Some highlights:

• Instant integration with leading agents: Works out of the box with ChatGPT, Claude, Cursor, Amazon Q, and Google Gemini.

• Enterprise-ready from day one: Scoped tokens, approval workflows, audit trails, and no infrastructure to manage.

• 100+ prebuilt MCP servers: Covering everything from Salesforce, Workday, and Atlassian to Box, Stripe, NetSuite, and even Reddit.

• 12,000+ connectors & 900,000 community recipes: Transform existing Workato automations into AI-ready “skills” without rewriting code.

• AI agents that do actual work: From HR onboarding (payroll setup, identity provisioning, SSO) to marketing pipeline generation (mining Gong calls, drafting Outreach sequences).

By comparison, rivals in the integration and automation space—think Zapier, MuleSoft, or even ServiceNow—have been slower to explicitly embrace MCP as the glue between agents and enterprise software. Workato is trying to seize first-mover advantage by not only embracing MCP but reimagining it as a fully managed service.

Big-Name Partners on Board

Workato isn’t going at it alone. The Enterprise MCP launch comes with endorsements and integrations from Anthropic, AWS, Atlassian, and Box.

• Atlassian says the combo unlocks autonomous actions across Jira and Confluence with enterprise-grade guardrails.

• Box is enabling multi-file analysis, search, and data extraction for AI agents working across enterprise content.

• Anthropic sees MCP powering Claude’s “intelligent, context-aware automation.”

In other words, Workato isn’t just launching a product—it’s building an ecosystem around MCP.

The Bigger Picture: The “Agentic Enterprise”

Workato has been talking a lot about the “Agentic Enterprise,” a vision where AI agents don’t just sit on the sidelines answering questions but actively run business processes across departments.

With Enterprise MCP, Workato claims it can now turn any of its 900,000+ automation “recipes” into MCP tools that AI agents can call securely. It’s the kind of infrastructure play that, if it works, could transform AI from a shiny demo into a backbone of enterprise operations.

The company argues this is the next logical step after a year of copilots and copilots-everywhere hype. “Trusted agents are not just a nice-to-have, but a requirement,” said Dave Marcus, Principal Analyst at Analysis.tech. “By building on its foundation in enterprise integration, Workato's MCP platform delivers high-quality, secure, and well-governed MCP services.”

Why This Matters for the Market

If Cadent’s predictive ad platform showed us how AI can sharpen media buying, and if ServiceNow’s AI push is about optimizing IT workflows, Workato is aiming at the plumbing—the orchestration layer that makes AI agents usable across the enterprise.

And in a fragmented AI ecosystem where every cloud vendor is pushing its own assistant, Workato’s MCP could become the neutral middle layer enterprises need. Think of it as the “USB standard” for AI agents. Without it, companies risk a spaghetti mess of custom integrations, compliance headaches, and brittle bots.

The question now: will Workato’s head start on MCP orchestration make it the default enterprise standard, or will cloud heavyweights eventually swallow the space whole? Either way, enterprises just got a clearer, safer path to put AI agents to work.

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Vocodia Holdings Corp (OTC: VHAI) is taking a bold step to reposition itself in the booming AI customer service market. The company announced today that Paul Taylor has been unanimously elected Chairman of the Board and interim COO, marking the start of a strategic pivot for its Digital Intelligence Sales Agent (DISA) platform toward collaborative AI networks.

The move comes as AI-driven service automation continues to surge. Analysts forecast the autonomous service market to reach $47 billion by 2030, with a growing share of routine transactions handled by intelligent agents. Vocodia aims to position DISA as a foundational “AI plumbing” layer, managing tasks from customer greetings and qualification to KYC checks and intelligent inquiry routing.

Leadership with Wall Street Credibility

Taylor brings more than three decades of public company turnaround and operational transformation experience. He has advised companies like EdgeMode (OTC: EDGM), Nukkleus (NASDAQ: NUKK), and MGT Capital Investments (OTC: MGTI), and co-founded S4TD LLC for strategic European investments.

“Paul is the ‘grown-up’ in the room,” said Vocodia CEO Brian Podolak. “His strategic vision and operational deal-making will be instrumental in repositioning Vocodia as a key component of collaborative AI networks.”

In his interim COO role, Taylor will oversee austerity measures and operational restructuring, aligning resources with strategic priorities while driving mergers, acquisitions, and shareholder value creation.

DISA’s Strategic Pivot

Vocodia’s pivot redefines DISA from a standalone SaaS contact center solution to a scalable integrative platform. By embedding itself into partner databases and collaborative networks, DISA aims to deliver cost-effective, agentic AI interactions at scale. This aligns with market trends emphasizing AI-assisted customer service, dynamic call routing, and networked support ecosystems.

Industry projections suggest that network-driven AI models could deliver 3-5x valuation multiples, leveraging recurring revenue and scalability. Vocodia’s focus on operational efficiency and strategic partnerships is designed to capitalize on these opportunities.

Looking Ahead

Taylor commented, “By building strategic partnerships and leveraging synergies, Vocodia will deliver innovative, scalable solutions that empower businesses and redefine customer experiences globally.”

With DISA’s integration into collaborative AI networks, Vocodia hopes to enhance market positioning, attract high-value partnerships, and generate sustainable revenue growth, positioning itself as a strategic leader in AI-driven customer engagement.

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Inriver is doubling down on AI with major updates to its Product Information Management (PIM) platform, offering brands more control over product content from onboarding to syndication. The new release introduces embedded AI agents, smarter workflows, and expanded distribution options designed to streamline operations and maintain brand consistency across channels.

AI-Powered Workflows and Content Management

Central to the update are two new AI agents—Inspire Generate and Translate—which collaborate with human teams to enrich and translate product information. GPT-5 is integrated directly into Inriver Inspire, allowing users to leverage advanced AI without leaving the platform. The system also incorporates brand terms, glossaries, and style guidance to ensure accuracy and consistency across all touchpoints.

“Our customers want to harness AI to streamline data ingestion, improve quality, and automate processes without losing trust or control,” said Rohit Goyal, CEO of Inriver. “With this release, we’ve embedded AI directly into workflows, empowering teams to model business processes into AI-driven automation while enhancing collaboration.”

Enhanced Syndication and Digital Shelf Accuracy

Inriver has also upgraded its syndication capabilities with Syndicate Advance, enabling flexible, channel-ready content delivery. New features include:

• Direct API connectivity to Best Buy

• ChannelEngine integration with access to 950+ channels and marketplaces

• Fully managed syndication service for automated, low-lift distribution

Paired with Inriver Evaluate, brands can now deliver accurate product information and monitor its performance across the digital shelf.

Streamlined Content Onboarding and Brand Store Updates

Content Onboarding has been revamped for faster, more accurate data imports, with auto-mapping, formula-driven transformation, error validation, and multilingual support reducing manual work and accelerating time-to-market.

The Brand Store now features smarter search, configurable templates, bulk downloads, public store links, and a built-in CDN for reliable, fast media delivery. The new open store capability allows sharing product content publicly without requiring logins or registrations.

Driving Revenue Through Product Data

With these enhancements, Inriver positions its PIM platform as a complete end-to-end solution, helping brands transform complex product information into revenue-driving assets.

Inriver will showcase the updates at PIMpoint 2025, demonstrating workflows from onboarding and enrichment to syndication, audit, and optimization.

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5W Public Relations is doubling down on digital. The New York-based PR agency has tapped two heavyweights from rival Zeno Group—Lauren McGuire as EVP of Digital & Social, and Clare Algozin as SVP of Paid Media—to strengthen its integrated campaign capabilities.

It’s a clear signal: in the high-stakes world of digital and social, 5WPR doesn’t just want to keep pace, it wants to sprint ahead.

The Digital Playmakers

McGuire, who spent more than a decade running digital operations across sectors from healthcare to travel, is known for building scalable systems that keep teams agile when platforms and algorithms shift overnight. At Zeno, she led operations and integration for ZDX, where her playbook was all about marrying emerging tech with efficiency.

Algozin, meanwhile, brings deep expertise in paid media, running multimillion-dollar budgets across social, search, programmatic, and video. Her edge? Using advanced targeting and AI-driven media buying to make campaigns both smarter and faster. She also has a knack for attribution modeling—the kind of data science that can separate real impact from vanity metrics.

Why It Matters

The hires come as agencies across the PR and ad landscape scramble to adapt to what feels like a constantly morphing media ecosystem. With influencer channels maturing, programmatic buying getting more complex, and brands demanding proof of ROI, agencies can’t afford to treat digital as an add-on—it’s the whole show.

Zeno itself has been on a tear in digital innovation, so poaching two of its senior players is a power move for 5WPR. For clients, it could mean more integrated campaigns that blur the lines between earned, paid, and social—a trend we’re seeing not just in PR, but across the martech industry.

The Bigger Picture

5WPR’s CEO Matthew Caiola calls the hires a mix of “operational excellence and strategic vision,” but the subtext is clear: agencies that don’t continually reinvent their digital chops risk falling behind. Competitors from Edelman to Weber Shandwick have been bulking up their own digital divisions, and with brand dollars shifting toward measurable, tech-powered campaigns, talent like McGuire and Algozin may prove to be the ultimate differentiator.

The takeaway? 5WPR is betting big on leadership that can cut through noise, optimize at speed, and—most importantly—translate complexity into results clients can actually measure. In today’s fragmented media landscape, that might be the only kind of PR that matters.

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When Snowflake, the AI Data Cloud giant, releases its annual Modern Marketing Data Stack report, the industry pays attention. The 2026 edition has spotlighted StackAdapt as a "company to watch" in the coveted Activation & Delivery: Paid Channels category—putting the programmatic ad tech player on the radar of marketers looking to supercharge their campaigns in an AI-first era.

Why This Matters

Snowflake analyzed marketing tech adoption patterns across more than 11,100 customers to map out which tools are shaping data-driven growth. The results paint a clear picture: AI, privacy, and data integration are no longer optional—they’re the backbone of modern marketing. Landing on Snowflake’s radar means StackAdapt is now grouped with platforms solving some of the industry’s biggest headaches: fragmented data, inefficient targeting, and measurement blind spots.

StackAdapt’s Angle

For StackAdapt, the recognition is validation of its strategy to give brands fast, secure ways to activate data across paid media channels. Yang Han, co-founder and CTO, put it bluntly: “Our work with Snowflake empowers marketers to activate data securely, efficiently, and at scale.” In other words, think less data drag, more precision targeting.

The company has been building momentum by helping brands unify audience insights and deliver campaigns with greater speed and accuracy. In a landscape where programmatic buying is increasingly automated by AI models, StackAdapt’s alignment with Snowflake suggests it’s gearing up to compete with bigger rivals by leaning into scale and agility.

Snowflake’s Stamp of Approval

Snowflake’s CMO, Denise Persson, noted StackAdapt’s “growth with Snowflake” as key to its recognition, highlighting its ability to meet “the ever-evolving needs of marketers.” Translation: the collaboration is less about buzzwords and more about real-world adoption, which has become the true differentiator as brands demand ROI over hype.

The Bigger Picture

Being named in Snowflake’s report doesn’t just hand StackAdapt bragging rights—it places the company within a shortlist of vendors shaping the next wave of AI-powered advertising infrastructure. With privacy tightening and competition heating up, the combination of StackAdapt’s paid channel focus and Snowflake’s AI Data Cloud could prove a timely advantage.

As marketers wrestle with how to blend personalization, compliance, and performance, StackAdapt’s recognition suggests its tools may help strike that balance. For a company that already pitches itself as the future of programmatic, Snowflake just gave it another layer of credibility.

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When Snowflake calls you a leader, it’s not faint praise. In its freshly released Modern Marketing Data Stack 2026 report, the AI Data Cloud heavyweight has crowned Alteryx a category leader in Analytics & Measurement for Business Intelligence.

The recognition places Alteryx in rarefied company—Snowflake’s report analyzed martech and adtech usage patterns from over 11,100 customers to identify which platforms are truly reshaping marketing workflows in an AI-driven world.

Why Alteryx Stood Out

AI and analytics are the backbone of modern marketing, but what separates contenders from leaders is how well they fuse accessibility with scale. That’s where Alteryx shines. Its no-code/low-code platform has long been popular with business analysts who want to slice and dice data without writing SQL scripts, and now its expanded partnership with Snowflake takes that capability a step further.

Enter Alteryx Live Query, now in public preview. The integration allows users to view, prep, and analyze Snowflake assets directly from the Alteryx One Platform—without pulling data out of the cloud. The result: no wasted time shuffling datasets, lower egress costs, and tighter governance controls. In practice, it means data scientists and marketers alike can query massive datasets, in real time, with speed and security intact.

As Alteryx CPO Ben Canning put it, the honor “underscores the power of our partnership with Snowflake and how we help teams adapt quickly, deliver more personalized experiences, and fuel transformation.”

From Marketing Theory to Practice

Alteryx isn’t just talking the talk; customers are walking the walk. Belgian telecom provider Telenet swapped out legacy CRM tools for the Alteryx + Snowflake combo and reported campaign build times slashed by 90%. Analysts saved six hours per week, freeing up bandwidth for hyper-personalized campaigns that improved NPS reach and delivered measurable impact.

That’s not just efficiency—it’s a competitive edge in a market where speed and personalization are non-negotiable.

Alteryx’s Own Test Case

Interestingly, Alteryx also eats its own dog food. Its marketing team pairs Snowflake data with Alteryx workflows and even integrates ChatGPT to craft data-driven campaigns at scale. CMO Michelle Huff noted the stack enables them to “quickly generate opportunities that drive pipelines and produce personalized content at scale.”

In other words, Alteryx is its own best case study.

The Bigger Picture

The Snowflake recognition validates what the industry has been seeing: data gravity is real, and the most valuable tools are the ones that let teams work with data in place, at speed, without forcing IT bottlenecks. Alteryx provides the user-friendly layer; Snowflake delivers the horsepower underneath.

For enterprises still drowning in siloed workflows, this partnership offers a template for modernization. And as AI-powered personalization, compliance, and performance measurement continue to collide, expect more marketers to take note of the Alteryx-Snowflake stack.

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