Revuze, an AI-powered market intelligence platform for CPG and retail, launched its Agentic AI offering, a solution that gives brands multiple ways to operationalize consumer intelligence through ready-made autonomous agents, direct integration into internal AI systems via the Model Context Protocol (MCP), and Vee, Revuze's conversational AI assistant.

The launch addresses a critical market gap. As Brands adopt AI copilots, most discover that general-purpose LLMs trained on unfiltered web data cannot reliably answer category-specific SKU-level questions. Revuze closes that gap with a validated data foundation built on a unified taxonomy of markets, categories, and products.

"Public LLMs are creative, but they lack the granular accuracy and market context that CPG and retail leaders need," said Guy Yair, CEO at Revuze. "We are giving them autonomous agents built on a foundation of domain expertise so brands can hook their AI systems into real consumer signals, rather than relying on hunches or hype."

Calculating Answers vs. Searching the Web

Not all AI insights are created equal. While generic LLMs answer product questions by retrieving and rephrasing arbitrary text found across the web, Revuze executes structured computational workflows over governed Voice of the Customer (VoC) data.

Instead of searching for a close-enough sentence online, Revuze agents mathematically calculate answers regarding exact volumes, star ratings, sentiment shifts, and SKU-level defects. This infrastructure delivers:

• Multi-Source Validation: Cross-references online reviews, social media, Product Detail Pages (PDPs), surveys, and customer care signals to create a single feedback loop.
• SKU-Level Depth: Continuously processes over 2.2 billion consumer signals, tracking more than 100 million products across 2,000+ categories.
• 90%+ Precision and Recall: Purpose-built VoC models yield verified, category-specific intelligence that brand teams can trust implicitly.

Three Pathways for Brand AI Deployment

Revuze's Agentic AI offers three flexible deployment options to fit any brand infrastructure:

• Open Integration Layer (MCP): Built on Anthropic's Model Context Protocol (MCP), allowing development teams to plug Revuze's verified domain data directly into custom internal LLMs and brand applications.
• Conversational Access (Vee): Powered by Anthropic's Claude, Revuze's assistant allows business users to query complex consumer feedback and receive instant, data-backed answers.
• Autonomous Execution: Out-of-the-box agents designed to independently analyze and automate workflows, including product launch tracking, returns issue detection, trend discovery, and competitive benchmarking

"We're acting as the missing layer under the AI stack," said Omer Kehat, VP Product. "Whether a brand wants an out-of-the-box agent watching for product issues, needs to fuel their own copilots or Claude via MCP, or wants their teams asking questions directly through Vee, we provide the foundation. MCP means a brand's internal AI doesn't need to figure out how to interpret messy consumer feedback, we've already done that work."