Fintel Connect has dropped a new reality check for financial marketers: in the AI era, banks are losing the visibility game—and affiliate publishers are winning it. The company’s latest industry report, Competing for Visibility in the Age of AI (2025/2026), breaks down how large language models source financial information and what it means for the institutions that depend on consumer discovery.

The key finding is blunt. More than 60% of AI-generated financial content comes from affiliate publishers, not the institutions that actually provide the products. While that may surprise traditional marketers, it aligns with a growing shift toward zero-click search, where AI summaries replace the need for a direct website visit.

AI Favors Affiliates, Not Banks

According to the study, AI systems consistently pull from consumer-facing financial guides produced by major affiliate players like NerdWallet, Bankrate, and Investopedia. These sites have spent years optimizing for credibility, structure, and breadth—features that large language models tend to reward.

Fintel Connect CEO Nicky Senyard says this shift underscores a larger change in how trust and visibility are built.

“Our goal has always been to help financial brands grow through partnerships grounded in transparency and performance,” Senyard said. “As AI changes how consumers search and trust information, affiliates are becoming a critical pipeline of information for the LLMs.”

That pipeline now has outsized influence. When AI tools summarize credit card options, savings rates, or loan products, the underlying data often originates from affiliate content—not the bank’s own site.

Zero-Click Search Is Reshaping Marketing Strategy

Financial marketers have traditionally relied on paid search, SEO, and direct site traffic to bring customers into the funnel. Zero-click search disrupts all three. Because AI-generated answers rarely require a click-through, visibility now depends on whether an institution’s product data appears in the sources AI trusts most.

Fintel Connect’s findings reinforce a trend that has been building across the search landscape. In the consumer tech sector, Google’s Search Generative Experience has already reduced traditional organic visibility for many brands. The financial industry is now facing a similar transition—but with higher regulatory stakes.

Affiliate publishers, with their deep content libraries and structured comparison formats, now serve as a primary point of entry for AI training models. Banks without strong affiliate pipelines risk slipping out of the conversation entirely.

Why Affiliates Are Winning the LLM Game

There are several reasons AI systems lean so heavily on affiliate content:

• Structured data formats make product comparisons easy to parse.

• Frequent updates ensure rate and offer information stays fresh—something AI models favor.

• High domain authority signals reliability to both search and AI systems.

• Consumer-first content language maps closely to the natural queries users ask LLMs.

Banks, by contrast, often struggle with rigid product pages, compliance-heavy language, and slower content updates. Even well-known institutions rarely produce the type of informational guides that AI systems prefer.

What This Means for Banks, Credit Unions, and Fintechs

The report suggests a clear path forward: strengthen affiliate relationships or risk disappearing from AI-driven financial discovery altogether.

Senyard notes that the research offers a roadmap for institutions adapting to fast-changing search mechanics. “This research gives financial institutions a window into that evolving landscape and shows how to strengthen affiliate relationships to ensure their products stay visible,” she said.

That visibility is now tied directly to revenue. If AI summaries highlight a competitor’s product because the model draws from affiliate comparisons, a bank may lose a customer before they ever reach its website.

In a marketplace where consumers increasingly trust AI assistants to filter financial options, product placement within affiliate content becomes a critical competitive lever.

The Bigger Industry Picture

Other sectors—insurance, travel, ecommerce—have experienced similar shifts. In each case, aggregators and comparison sites became gateways to visibility long before AI arrived. The financial industry is now confronting the AI-enhanced version of that trend.

With regulatory pressures pushing institutions toward clearer disclosures and more standardized information, the affiliate model may become even more influential. AI tools prefer consistency, and affiliates offer it at scale.

A New Playbook for Financial Visibility

Fintel Connect’s report signals that the era of controlling your own digital visibility through owned content is fading. The companies that adapt quickest will treat affiliate ecosystems not as optional marketing channels but as essential infrastructure for AI relevance.

The takeaway is simple: If financial brands want to shape AI-generated search results, they must ensure their product data lives where AI systems are already looking.

And right now, that place is not their own website.

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Premier CX and CommBox have teamed up to tackle one of hiring’s biggest bottlenecks: inconsistent, slow, and siloed communication with job candidates. Their new platform, JourneyHub™, aims to bring order—and intelligent automation—to the chaotic world of recruitment messaging.

The service merges Premier CX’s expertise in experience design with CommBox’s AI-powered engagement engine. Unlike traditional tools that rely on email blasts or manual follow-ups, JourneyHub™ centralizes messaging across WhatsApp, SMS, email, voice, and other channels. The goal is simple: deliver real-time, personalized updates without demanding more time from overwhelmed hiring teams.

A Smarter Layer on Top of ATS Systems

One of JourneyHub’s biggest differentiators is its ability to work hand-in-hand with major Applicant Tracking Systems. Rather than replacing systems like Greenhouse, Workday, or SAP SuccessFactors, it enhances them by adding an intelligent communication layer on top. For recruiters, that means fewer dropped messages, fewer no-shows, and a more predictable hiring workflow.

Anthony Buxton, CEO of Premier CX, says the platform is designed to improve both speed and experience. “JourneyHub™ is about making recruitment communication smarter, faster, and more human,” he said. By blending human-centric design with AI-driven automation, the platform aims to reduce friction and shorten the time it takes to fill open roles.

CommBox CEO Dvir Hoffman echoes the point. “This collaboration sets a new standard for recruitment communication,” he said. In an era when candidates expect instant, accurate answers across any channel, Hoffman argues that a unified communication backbone is no longer optional.

Blending Automation With Human Insight

JourneyHub™ relies on advanced automation to streamline repetitive tasks, but it doesn’t neglect personalization. Recruiters can build custom workflows that reflect their brand voice, tailor messages to different roles, and adapt communication formats to candidate preferences.

The platform’s AI agents can handle FAQs, provide application updates, and respond instantly around the clock—making it a direct fit for industries where hiring moves quickly and candidates often drop out early due to silence or slow follow-up.

Core Features Highlighted

The companies outlined several capabilities designed to strengthen the recruiter-candidate relationship:

• AI-Powered Automation: Smart workflows and AI agents cut manual work and accelerate hiring.

• Omnichannel Communication: All channels—WhatsApp, email, SMS, voice, and more—managed through a single interface.

• Personalised Candidate Journeys: Messages tailored to each brand’s tone and each applicant’s journey.

• Seamless ATS Integration: Compatible with platforms including Greenhouse, Workday, and SAP SuccessFactors.

What It Means for the Recruitment Tech Market

The launch comes as recruitment teams face rising pressure to respond faster, deliver transparency, and compete for scarce talent in high-turnover sectors. AI-driven candidate communication has become one of the most active areas in HR tech, with platforms racing to offer more intuitive, more immediate engagement tools.

JourneyHub™ positions itself as a hybrid solution: automated enough for efficiency, yet structured enough to preserve brand identity and empathy. Its omnichannel design also reflects a broader industry shift, as candidates increasingly prefer messaging apps over traditional email chains.

Debuting at TATech Europe 2025

JourneyHub™ will make its public debut at TATech Europe on November 11–12, where it’s poised to attract attention in a field hungry for solutions that cut time-to-hire. If early claims hold up, the platform could quickly become a benchmark for AI-powered recruitment engagement.

For now, JourneyHub™ enters the market with a clear message: in hiring, communication isn’t just a touchpoint—it’s the experience.

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Transcend just earned a major validation in the rapidly evolving privacy tech landscape. The company has been named a Leader in the IDC MarketScape: Worldwide Data Privacy Compliance Software 2025 Vendor Assessment, a recognition that pushes it to the front of an industry racing to automate compliance and support AI-driven data operations.

IDC highlights Transcend’s strength across consent management, data mapping, DSR automation, and enterprise-scale privacy orchestration—areas where many first-generation tools still rely heavily on manual processes. The report also points to Transcend’s deep API and integration capabilities, which allow it to slot into sprawling digital infrastructures without forcing redesigns or long deployment cycles.

Automation as a Competitive Edge

According to Ryan O’Leary, Research Director for Privacy and Legal Technology at IDC, enterprise buyers increasingly want platforms that eliminate repetitive compliance tasks. That’s where Transcend stands out.

“Transcend fully automates many of the cumbersome and menial aspects of compliance,” O’Leary noted. He added that the company is often chosen for its ability to deploy quickly, support complex multi-layered organizational structures, and scale across thousands of domains—requirements that large global enterprises can’t afford to compromise on.

It’s no longer enough to track privacy obligations; enterprises now need systems that act on them in real time.

Privacy Meets Growth—Not Friction

Transcend CEO Ben Brook frames the recognition as part of a broader shift in how enterprises think about data. Rather than treating compliance as a barrier, companies are beginning to see how structured, well-governed data workflows can accelerate AI initiatives and improve customer trust.

“We believe this recognition validates our vision for a new era of user data,” Brook said. He emphasized that responsible data use, executed with the help of unified automation, can unlock new opportunities instead of limiting innovation.

This perspective is gaining traction across sectors adopting AI models that demand higher-quality, well-classified, and well-governed data.

Full-Stack Consent Management Gets the Spotlight

The MarketScape report singles out Transcend’s full-stack approach to consent management as a major differentiator. Unlike plug-in solutions that handle only front-end collection, Transcend extends automation across the entire lifecycle—discovery, orchestration, enforcement, and auditability.

Key capabilities include:

• Real-time network-layer blocking of unauthorized trackers

• Customizable banners for multiple brands and regions

• Deep integrations across web, mobile, and back-end systems

• Support for both authenticated and anonymous users

As global regulations expand, from GDPR and CPRA to sector-specific privacy mandates, enterprises need systems that adapt without constant engineering work. Transcend’s architecture appears designed with that future in mind.

Built for Enterprise Scale

The report also emphasizes Transcend’s integration framework. With more than 200 prebuilt integrations, developer toolkits, and customizable automation functions, the platform supports advanced privacy operations that extend across cloud apps, infrastructure, and business workflows.

For customers, IDC notes, this flexibility translates into smooth, fast implementations—something notoriously rare in privacy software deployments. Interviewed users described Transcend’s onboarding experience as a standout improvement over past tools they’ve used.

Why This Recognition Matters

IDC’s MarketScape assessments carry significant weight, particularly in categories where compliance risk and technical complexity converge. As enterprises scale AI initiatives and face increasing regulatory scrutiny, the need for fully automated privacy operations is becoming non-negotiable.

Transcend’s positioning as a Leader suggests that the market is shifting toward platforms engineered for deep automation, developer-friendly extensibility, and long-term interoperability across global digital estates.

For companies carrying the weight of thousands of data systems—and millions of customer relationships—this recognition may signal which vendors are built for the AI-driven decade ahead.

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Mitel is pushing deeper into AI-enabled communications with the global debut of Mitel Workflow Studio, a low-code/no-code platform designed to automate complex communication processes without requiring engineering muscle. The move arrives as enterprises accelerate hybrid communications deployments and fold AI into daily operations—an evolution Mitel wants to simplify rather than complicate.

Workflow Studio blends drag-and-drop simplicity with serious automation power. Users can build workflows that handle AI-driven call routing, real-time language localization, visitor registration, transcription, scheduling, and more. The interface leans heavily on usability, giving non-technical teams the ability to deploy automation that once required specialist development.

Meeting the Moment for AI-Driven Communications

Enterprise communication strategies are shifting quickly. Techaisle recently reported that 53% of organizations are integrating AI into their communications stack. Mitel positions Workflow Studio as the bridge between traditional UC systems and the next generation of intelligent automation.

The platform embeds directly into Mitel’s UC solutions but also connects across a wide spread of third-party tools: Microsoft 365, Zoom, Slack, Zendesk, Salesforce, and others. On the AI side, it taps leading LLMs including ChatGPT, Google Gemini, and Anthropic Claude. This combination gives enterprises a practical way to deploy AI where it matters most—call flows, customer engagement, internal communication, and operational efficiency.

Martin Bitzinger, Mitel’s SVP of Product Management, says the platform is built to remove long-standing roadblocks. “Workflow Studio removes major roadblocks, like a lack of access to advanced GenAI tools or a large development team,” he said. With communication now central to customer satisfaction and employee productivity, Bitzinger positions Workflow Studio as a strategic lever that helps organizations adapt quickly without costly software investments.

Real-World Impact: Heilig Hart Hospital

Mitel points to Belgium’s Heilig Hart Hospital as an early proof point. Serving 850 staff and hundreds of daily patient interactions, the hospital used Workflow Studio to convert voicemail messages to text in real time. The shift reduced response times and helped support teams prioritize care faster.

Benjamin Peeters, the hospital’s IT Director, said the low-code approach was key. “Its low-code approach allowed us to quickly implement custom workflows without needing extensive technical skills,” he noted. The seamless integration with Mitel’s existing systems also delivered a cost-efficient way to boost communication quality for both staff and patients.

What Workflow Studio Brings to the Table

Mitel is pitching Workflow Studio as both an enterprise automation engine and a way to democratize development. Key capabilities include:

• Automation for Efficiency: Build workflows that route calls, send alerts, and update records to save time and reduce errors.

• GenAI-Powered Workflows: Enhance experiences with intelligent automation driven by LLMs and Mitel’s API framework.

• Cross-System Integration: Connect business processes and unify disconnected tools through customizable workflows.

• Faster Development Cycles: Use an intuitive visual designer to deploy new functionality with minimal IT dependency.

These features reflect a larger industry trend: AI and workflow automation are no longer experimental—they’re structural. Aragon Research’s Jim Lundy notes that automation has moved “from innovation labs to the boardroom,” and says Workflow Studio gives enterprises a way to embed intelligence directly into communications strategies.

A Platform With Room to Expand

Mitel plans to integrate Workflow Studio across its broader ecosystem. It’s available today as a standalone platform or paired with Mitel CX, the company’s next-gen AI-driven customer experience suite. Support for OpenScape will arrive in Q1 2026, signaling continued expansion across Mitel’s portfolio.

With Workflow Studio, Mitel is making the case that high-impact automation shouldn’t be gated behind technical expertise. By fusing low-code tools with GenAI and deep integrations, the company is offering a streamlined path for enterprises looking to modernize communications—and stay agile in a market where speed and intelligence increasingly define competitive advantage.

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Strike Graph has landed a coveted spot in the AWS Startups: Building with Llama program, a six-month, invite-only initiative created by AWS and Meta to accelerate innovation on Llama, Meta’s fast-growing open-source AI ecosystem. Only 33 startups nationwide made the cut—just 3% of more than 1,000 applicants—placing Strike Graph among the top AI companies shaping real-world enterprise solutions.

For a sector long plagued by checklists, spreadsheets, and reactive controls, Strike Graph represents a radically different vision of compliance: one fueled by agentic intelligence, dynamic data models, and continuous verification.

Reimagining Compliance With Adaptable AI

Founded in 2020 by technologist Justin Beals, Strike Graph was built around a simple but disruptive premise: compliance frameworks shouldn’t be static. Regulations shift, attack surfaces evolve, and enterprise systems change too fast for manual processes. Strike Graph addresses that gap with an AI-native platform designed to adapt in real time.

Instead of treating compliance elements as isolated artifacts, the company uses dynamic ontologies and graph-based data models to map risks, controls, evidence, and frameworks as interconnected but distinct entities. This architecture unlocks AI-driven automation at scale, allowing agentic systems to interpret, test, and validate compliance requirements continuously.

The result is a platform engineered not just to pass audits but to transform compliance into a strategic, ongoing advantage.

The AI Features Behind Strike Graph’s Momentum

Strike Graph’s placement in the Llama program underscores the maturity of its AI stack. Several capabilities stand out:

• Agentic AI Architecture: Powers adaptive, context-aware workflows that evolve with regulatory and business environments.

• Verify AI: A patent-pending internal auditor that monitors and validates controls in real time.

• AI Security Assistant: Delivers instant, privacy-safe answers to compliance queries and assists in incident response.

• AI Automation: Syncs evidence collection with cloud deployments to speed audit readiness.

• Multi-Framework Mapping: Automatically correlates controls and evidence across 40+ frameworks to eliminate redundancy.

• Zero-Trust AI Stack: Keeps compliance data fully encrypted and avoids external third-party dependencies.

These tools give enterprises automated visibility across complex environments and allow teams to shift from reactive reporting to proactive assurance.

A Strategic Boost From AWS and Meta

With access to Llama experts from both AWS and Meta, Strike Graph will be able to accelerate development around automated evidence collection, contextual risk analysis, and real-time compliance verification. For companies wrestling with sprawling regulatory demands, these enhancements could dramatically reduce manual workload and improve audit accuracy.

CEO Justin Beals says the recognition validates the company’s mission. “Joining the Building with Llama program allows us to push our AI capabilities even further, all in service of helping companies build and maintain trust with their customers,” he noted.

For AWS and Meta, investments like this also signal a broader trend: open-source LLMs are increasingly becoming the backbone of enterprise-grade automation. By selecting startups with deep technical foundations, the program aims to catalyze the next era of AI-native software—especially in highly regulated sectors.

Strike Graph’s inclusion suggests one thing clearly: in the race to modernize compliance, the companies tying AI directly into the foundation of their architecture will be the ones defining the category.

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Qlik has secured a Leader position in the IDC MarketScape: Worldwide Data Integration Software Platforms, 2025 Vendor Assessment, marking a strong validation of its strategy as enterprises race toward real-time, AI-ready data ecosystems. The recognition highlights a clear industry shift: data teams no longer want just faster ingestion or cleaner pipelines—they want both, without locking themselves into a rigid cloud stack.

The IDC report points to growing demand for real-time change data capture, governed self-service access, visible data lineage, and AI-infused workflows. Qlik argues its unified platform delivers all of these while staying cloud-agnostic, a competitive advantage as enterprises rethink their architectures for a hybrid world.

Real-Time Data, Zero Lock-In

“Data leaders want two outcomes at once—make trusted data available faster and keep architectures open,” said Drew Clarke, EVP of Product & Technology at Qlik. The company positions itself at this intersection with a platform that blends streaming ingestion, ELT/ETL, catalog-led governance, and built-in AI tools.

Unlike platforms tied to a single cloud ecosystem, Qlik supports AWS, Azure, Google Cloud, and client-managed deployments equally. This flexibility increasingly matters as teams diversify workloads and avoid single vendor dependence.

AI Hits the Data Engineering Workflow

The IDC assessment also highlights Qlik’s agentic and generative AI assistance, embedded directly inside data engineering tasks. Instead of bolt-on AI features, Qlik integrates intelligence within the pipeline, offering:

• Prompt-to-SQL generation

• Context-aware rule suggestions

• Automated documentation

• API contract guidance

• Support for vectorization and RAG pipelines

• Integrations with LLMs and vector databases

These capabilities push Qlik deeper into AI-enabled data ops—a space heating up fast as enterprises lean on automation to stay competitive.

Catalyst for the Open Lakehouse Era

Qlik’s backing of Apache Iceberg stands out, aligning with a broader market movement toward open table formats. The platform supports Iceberg ingestion, optimization, compaction, and hybrid patterns that bridge old environments with modern lakehouse architectures. Its roadmap includes more in-flight transformations and expanded cross-cloud operability, signaling continued investment in openness.

Industry analysts see this as a differentiator. Stewart Bond, VP of Data Intelligence and Integration Software Research at IDC, noted that real-time, hybrid, multi-cloud capabilities are becoming defining factors in enterprise data modernization. Qlik’s placement as a Leader,, he added, reflects its momentum in delivering “trusted, governed, and AI-ready data pipelines.”

Customer Validation From the Front Lines

Enterprises already moving toward real-time operations say Qlik delivers measurable impact. “Qlik lets our teams move data continuously and make it usable with policy we can see,” said Colton Porter, Manager of Advanced Planning Systems at MillerKnoll.

He emphasized that engineers and analysts now operate from shared products with clear lineage and quality, modernize to Iceberg without friction, and use embedded AI to validate and improve pipelines. It’s a practical approach, he said, to accelerate analytics and AI “without trading away governance.”

Why This Matters

Qlik’s recognition comes at a moment when the data integration market is undergoing rapid transformation. Vendors are racing to combine:

• Real-time data movement

• End-to-end governance

• Open standards

• AI-native design

• Hybrid cloud freedom

Few platforms check all the boxes. Qlik’s strategy—centered on flexibility, openness, and embedded AI—positions it as a strong contender as enterprises re-architect for the next generation of data and AI workloads.

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6sense has introduced the most transformative update in its history. The company unveiled RevvyAI, a next-generation intelligence layer designed to serve as a central command center for the entire go-to-market engine. With this launch, 6sense shifts from being a data-driven orchestration platform to becoming the operational nervous system for modern revenue teams.

RevvyAI marks a significant moment for GTM technology. AI adoption has accelerated across sales, marketing, and revenue operations, yet teams still fight fragmented data, slow workflows, and limited visibility. RevvyAI targets these gaps with a unified AI partner that helps teams move faster, prioritize smarter, and focus on actions that drive measurable revenue.

A New AI Experience for Revenue Teams

RevvyAI reshapes how users interact with the 6sense platform. At the core is a conversational experience that removes the friction of traditional dashboard navigation. Users can launch campaigns, tune signals, build audiences, or generate reports by simply describing what they want. The interface interprets intent, guides decisions, and reveals insights that would otherwise stay buried.

This shift matters. Most GTM platforms claim automation, yet many still require complex workflows and manual setup. RevvyAI compresses those steps with natural-language execution. As a result, even non-technical teams can deploy advanced plays without relying heavily on operations support.

Specialized Agents Built for Every GTM Motion

RevvyAI introduces a set of always-on AI agents built to support core revenue functions. Each agent focuses on a different slice of the funnel, offering deeper analysis and hands-off execution.

The Ad Campaign Companion evaluates performance data and designs new campaigns that improve efficiency. It optimizes spend, highlights gaps, and identifies better targeting opportunities based on real buying behavior.

The Keyword Advisor monitors search and campaign data in real time. It identifies emerging patterns, recommending new keyword and content strategies as buyer interests shift. This agent acts as a dynamic SEO engine that evolves with demand signals.

The 6QA Analyst evaluates qualification criteria, buying signals, and pipeline activity. It surfaces next-best actions for sales and marketing teams, reducing the busywork of manual analysis and bringing clarity to prioritization.

Together, these agents deliver a coordinated assistive layer that helps teams adapt quickly, uncover new opportunities, and reduce operational drag.

Custom Workspaces Designed for How Teams Work

Another major upgrade is the addition of Persona-based Agentic Workspaces. These workspaces allow organizations to tailor the platform for specific roles. Sales teams can unify agents, signals, and workflows aligned to outreach and pipeline acceleration. Marketing teams can group data sources, AI assistants, and reporting tools to support campaign execution.

This flexibility reflects a broader industry trend. GTM platforms are moving away from one-size-fits-all dashboards and shifting toward curated environments that support specialized motions. RevvyAI aligns with this movement by providing modular, role-aware interfaces.

Reinventing GTM Execution with Transparency and Control

RevvyAI arrives alongside several platform upgrades aimed at improving visibility and governance across GTM operations. These updates expand the breadth of signals, improve predictive scoring, automate inbound traffic qualification, and enhance sales intelligence.

Signal Expansion introduces configurable signals, prompt-based discovery, buying group objects, and new data sources. Teams gain a clearer picture of who is in market and why.

Customizable and Transparent Scoring provides deeper explainability around predictive models. Users can now understand the “why” behind recommendations and refine scoring logic to match their unique processes.

Workflow Intelligence brings prompt-driven nodes, partner extensions, and event-based triggers. These improvements help teams build more adaptive workflows that respond to real-time behavior rather than static rules.

Agentic-led Inbound takes aim at conversion inefficiencies. The platform identifies, qualifies, and routes buyers automatically, turning website traffic into meetings with minimal manual intervention.

Lastly, 6sense has added Sales Intelligence Enhancements that layer RevvyAI insight into every touchpoint. Teams receive contextual summaries, improved accuracy, and deeper recommendations across contacts, opportunities, and segments.

A Significant Step Forward in the GTM AI Race

RevvyAI represents more than a product release. It marks 6sense’s move toward a more expansive role as a GTM operating system built around agentic AI. The timing aligns with a broader market shift. B2B companies are pushing for efficiency, clarity, and predictable growth. They want AI-driven precision without losing strategic control.

Chris Ball, 6sense CEO, highlights this tension. Revenue leaders must prove both efficiency and growth. RevvyAI aims to deliver both by compressing execution time and improving pipeline quality.

Competition in the GTM AI space is rising quickly. Rivals are investing in autonomous agents, dynamic scoring, and real-time intelligence. However, 6sense’s ability to pair these innovations with existing intent data and orchestration capabilities gives it a notable advantage. The platform already sits at the center of many enterprise revenue stacks, making RevvyAI an upgrade rather than a replacement.

Early Access Begins at Breakthrough 2025

Attendees at Breakthrough 2025 in Las Vegas will get the first look at RevvyAI. Early users will test conversational workflows, evaluate agents, and preview deeper AI connections across the platform. The rollout signals a new chapter for 6sense as it moves toward a more automated, agentic GTM model.

The introduction of RevvyAI underscores a simple reality. Revenue teams need more than dashboards. They need strategic intelligence, faster decision cycles, and AI that can handle the operational weight. RevvyAI brings that vision closer, offering a glimpse of what fully AI-driven GTM execution could look like in the coming years.

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Bloomreach is giving product-listing pages a much-needed upgrade. The company unveiled Personalized Media in-Grid, a new capability that transforms traditional product grids into dynamic storytelling environments. Instead of static rows of items, retailers can now weave videos, buying guides, promotions, and intelligent recommendations directly into the browsing experience.

The update builds on Bloomreach Discovery, the company's AI search solution, and extends the platform’s connected value across marketing and conversational commerce. The result is a more fluid, contextual shopping journey that merges discovery, education, and personalization—without adding engineering overhead.

This release arrives as retailers push for higher engagement and more curated online experiences. Product-listing pages still generate massive traffic, but most remain functional rather than persuasive. Bloomreach sees this as untapped real estate for narrative-driven commerce.

Turning Grids Into Guided Experiences

Personalized Media in-Grid allows merchandisers to place rich content between search results and category listings. Instead of forcing shoppers to leave the grid to learn more, retailers can surface videos, how-to guides, seasonal themes, and cross-sell prompts right where decisions happen.

Jordan Roper, GM and VP of Product for Bloomreach Discovery, says the goal is simple: give retailers a way to turn every scroll into a moment of relevance. Today’s shopping journey blends inspiration with intent, and the new feature helps retailers meet shoppers with content that informs and nudges purchase decisions.

Built for Scale — Without Extra Engineering

Bloomreach’s approach prioritizes usability at scale. Merchandisers can choose the exact slot placement, preview changes in context, and schedule content across categories or queries. After the initial integration, teams can manage the entire experience without additional development support.

This shift matters. Many brands struggle to customize PLPs without constant engineering work. Personalized Media in-Grid brings no-code control to a traditionally rigid surface, allowing marketing and merchandising teams to move faster and test more.

Precision Targeting and Personalization

The new capability connects with Bloomreach Engagement and Bloomreach Clarity, enabling targeted content delivery and conversational experiences. Retailers can tailor messages to specific audiences or trigger personalized recommendations through the platform’s segmentation and AI models.

It’s a move that brings Bloomreach closer to a fully agentic shopping platform—one where AI governs not just search and recommendations, but placement, messaging, and real-time shopper interactions.

Measuring What Matters

Performance tracking is built in through Discovery’s analytics, with extended reporting available in Engagement dashboards. Retailers can assess which content formats drive higher engagement or conversion, giving them clearer insight into how storytelling impacts revenue.

A Strategic Step for Retail AI

With AI reshaping the retail ecosystem, Bloomreach’s update positions product grids as a new frontier for engagement. Rival platforms have layered personalization into recommendation engines, but few have reimagined the grid itself. Personalized Media in-Grid turns this overlooked space into a programmable, adaptive channel — one that blends branding and commerce without interrupting the buying flow.

For retailers seeking stickier PLPs and higher conversion across product-heavy pages, this feature delivers a direct path to more immersive and personalized shopping.

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