Azoma Launches Agentic Merchant Protocol (AMP) to Boost E-commerce Visibility for AI Agents, Trusted by L'Oréal, Unilever, Mars, and Beiersdorf
E-commerce startup Azoma has introduced the Agentic Merchant Protocol (AMP), a new framework designed to make products visible to AI agents, which are projected to handle 10-20% of U.S. commerce spend by 2030, according to Morgan Stanley. AMP aims to provide high-volume retailers, including grocery, electronics, and fashion brands, with a "brand-friendly" presence in an e-commerce landscape increasingly influenced by autonomous shoppers. The system simplifies product information management by allowing brands to input data once into Azoma's platform and distribute it across various online marketplaces and product listing aggregators, including pages optimized for AI agent search and retrieval. This addresses the current challenge where AI agents often synthesize product information from unverified sources, offering minimal brand oversight with existing siloed AI integration systems like OpenAI’s ACP or Google’s UCP.
The e-commerce landscape is undergoing a significant transformation, with the primary customer evolving from a human behind a screen to the AI agents they deploy. Investment banking giant Morgan Stanley projects that 10-20% of the entire U.S. commerce spend could be agentic by 2030, translating to a market value of $190 billion to $385 billion. In response to this shift, four-year-old agentic AI e-commerce startup Azoma has unveiled its Agentic Merchant Protocol (AMP).
This new framework is specifically designed for high-volume retailers, such as grocery brands, electronics manufacturers, and fashion labels, aiming to provide them with a "brand-friendly" anchor in an ecosystem increasingly dominated by autonomous shoppers. The core idea behind AMP is compelling and straightforward: it streamlines the process of managing product information online.
Currently, merchants selling physical products online are required to manually enter details like SKUs and materials across various online marketplaces and product listing aggregators, including platforms like Walmart, Amazon, and Google Shopping. Azoma's AMP system eliminates this manual redundancy. Brands can now input all their product information into Azoma's platform once, and the system will then push it out to all necessary destinations. This includes pages specifically optimized for AI agents to search and retrieve information for users, enabling them to recommend products that precisely fit a user's specific query.
AMP seeks to end the 'black box' era of early agentic AI e-commerce. Modern AI integration often relies on siloed systems such as OpenAI’s ACP or Google’s UCP. While these protocols facilitate the technical handshakes necessary for product discovery and payment, they offer limited oversight regarding brand integrity. When an AI agent, deployed by a customer, attempts to understand and respond to a human consumer's product query, it frequently synthesizes data from unverified sources across the web, including platforms like Reddit or outdated affiliate sites. Azoma's AMP aims to provide a more controlled and brand-aligned data source for these AI agents.