Botify Launches ‘Agentic Feeds’ to Power Machine-Driven Product Discovery via OpenAI’s Commerce Protocol
Botify Launches ‘Agentic Feeds’ to Power Machine-Driven Product Discovery via OpenAI’s Commerce Protocol
As consumer search habits shift toward AI assistants, Botify has unveiled Agentic Feeds to optimize product data for AI-driven commerce. By adopting emerging standards like OpenAI's Agentic Commerce Protocol (ACP), the platform helps retailers ensure their products are structurally prepared to be discovered and recommended by autonomous shopping agents.
The infrastructure of digital commerce is undergoing a foundational shift. The era of the search-driven shopper—typing queries into a search engine and parsing through blue links—is rapidly giving way to machine-driven discovery, where autonomous AI agents curate, evaluate, and even purchase products on a user's behalf.
In response to this paradigm shift, enterprise search and discoverability platform Botify announced the launch of Agentic Feeds on March 24, 2026. The new product is designed to automate the creation and delivery of AI-optimized product data feeds, ensuring brands remain visible in an ecosystem increasingly dominated by protocols like OpenAI’s Agentic Commerce Protocol (ACP) and Google’s Universal Commerce Protocol (UCP).
The Rise of Agentic Commerce
The launch arrives at a critical juncture for online retailers. OpenAI, in partnership with payment processor Stripe, has aggressively pushed the Agentic Commerce Protocol (ACP)—an open-source standard enabling programmatic commerce flows between AI agents, buyers, and businesses. Through ACP, platforms like ChatGPT can ingest structured catalog data, understand real-time inventory, and surface relevant products contextually within conversational interfaces.
However, a stark disconnect has emerged between retailer infrastructure and AI requirements. According to Botify, AI bot traffic to retail sites surged 5.4x in 2025 alone. Yet, internal research co-authored with AWS and DataDome reveals a sobering reality: being crawled by an AI model is no longer synonymous with being discovered. AI systems ingest vast amounts of data internally to evaluate products but rarely send traditional referral traffic back to the retailer unless the data perfectly matches their structural requirements.
“AI agents don’t discover products the way search engines do; they evaluate your web content and structured data to make decisions,” explained Joe Doran, Chief Product Officer at Botify.
Closing the Visibility Gap
This architectural mismatch has created what industry experts are calling a "visibility gap." Legacy product feeds, originally designed for traditional search engines and basic shopping widgets, lack the depth, nuance, and adaptability required by modern Large Language Models (LLMs).
When a consumer asks an AI assistant to "find the best running shoes for flat feet under $150 with a generous return policy," the AI doesn't just look for keywords. It cross-references product specs, user reviews, Q&A sections, and merchant policies. If a retailer’s product feed strips away this deep context, the AI simply skips it, leaving even top-tier products excluded from AI-driven recommendations.
Agentic Feeds directly targets this gap. By leveraging Botify's proprietary crawl intelligence and cached site content, the platform builds protocol-compliant product data that meets the exact structural demands of ACP and UCP.
How Agentic Feeds Rebuild Product Data
Botify's new framework is engineered to complete three core functions for enterprise brands:
- Contextual Enrichment: It automatically enriches standard product feeds with high-value context—such as user reviews, Q&A data, and granular product attributes—that AI agents rely on to form accurate, trustworthy recommendations.
- Protocol Adaptability: Because the standards for agentic commerce are still evolving, the feeds are dynamically designed to adapt as OpenAI, Google, and other major players update their commerce protocols.
- Measurement and Optimization: Moving beyond traditional clicks and impressions, Agentic Feeds includes tools to measure the direct impact of enriched data on AI visibility and actual product selection rates.
By converting a brand's digital footprint into "AI-ready" data, retailers can transition from passively hoping their pages rank to actively feeding structured, high-intent data into the models making purchasing decisions.
The Broader Implications for Retail Strategy
The adoption of open commerce standards marks a pivotal moment in the evolution from search engine optimization (SEO) to generative engine optimization (GEO). The integration of secure tokenized payments directly within AI chats means the distance between product discovery and checkout is collapsing.
Consumers are already leaning into this reality; Botify's data indicates that 73% of consumers are using AI assistants, with 38% explicitly using them for shopping tasks. As the frictionless, in-chat checkout experience becomes the new baseline, the brands that win will be those that establish themselves as trusted, perfectly structured data sources for autonomous agents.
Agentic Feeds is currently in tech preview for a select group of enterprise clients—including one major retailer already utilizing the system to deliver AI-optimized feeds for over one million products. General availability is slated for the second half of 2026. For digital marketers and commerce leaders, the mandate is clear: adapt your data for the machines, or risk invisibility in the next era of the internet.