Source: VentureBeat

Agentic Commerce: Azoma’s Agentic Merchant Protocol (AMP)

For future‑focused e‑commerce brands, the primary customer is rapidly changing from a person behind a screen to the AI agents that the human customer deploys on their behalf to research and—if projections are correct—purchase the product.

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The Emerging Landscape

• Morgan Stanley research predicts 10‑20 % of total U.S. commerce spend could be agentic by 2030, equating to $190 B‑$385 B.
• This shift signals a move from human‑centric browsing to autonomous shoppers that act on behalf of consumers.

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Introducing the Agentic Merchant Protocol (AMP)

Azoma, a four‑year‑old agentic‑AI e‑commerce startup, has unveiled AMP, a framework that gives high‑volume retailers—grocery brands, electronics manufacturers, fashion labels—a “brand‑friendly” anchor in an ecosystem increasingly dominated by autonomous shoppers.

Core Idea

Instead of manually entering product details (SKUs, materials, etc.) on each marketplace (Walmart, Amazon, Google Shopping, etc.), brands can:

1. Upload all product information to Azoma’s platform.
2. Push the data everywhere it’s needed, including pages optimized for AI agents to search, retrieve, and recommend products that match specific user queries.

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Using Technology to End the “Black Box” Era

Modern AI integration typically relies on siloed systems such as OpenAI’s ACP or Google’s UCP. While these protocols handle discovery and payment handshakes, they provide minimal oversight of brand integrity.

• AI agents often synthesize data from unverified corners of the web (Reddit, outdated affiliate sites, etc.), creating a “black box” where the brand’s intended messaging is lost.

AMP functions as a high‑level “system of record”, bridging disparate platforms and allowing companies to centralize product intelligence—including legal guardrails and brand books—into a single, machine‑native format.

“AMP breaks the foundations of traditional ecommerce,” states Max Sinclair, CEO of Azoma, in a press release shared with VentureBeat ahead of the official announcement (March 12, London).
“For decades, marketplaces like Amazon and Walmart acted as gatekeepers by controlling product detail pages, rankings, and distribution. Brands optimized a finite set of endpoints: PDPs, ads, search results. In an agentic world, those fixed pages no longer exist.”

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Target Sectors

Azoma’s platform is engineered for high‑volume retailers and manufacturers of physical goods, with a primary focus on:

• Consumer Packaged Goods (CPG)
• Fast‑Moving Consumer Goods (FMCG)

In an interview with VentureBeat, Sinclair clarified that AMP does not currently support:

• NFTs
• SaaS products
• Financial sectors (banking, insurance)

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Sovereignty in a Multi‑Agent World

A coalition of consumer‑goods giants—L’Oréal, Unilever, Mars, Beiersdorf, and Reckitt—has already adopted AMP. For these organizations, maintaining a consistent identity across AI surfaces is an urgent priority.

“The fact that businesses like L’Oréal, Unilever, Mars & Beiersdorf have moved so quickly to adopt AMP tells you everything about the urgency they feel,” Sinclair remarked. “These are companies that have spent decades building brand equity—they’re not about to hand control of how their products are represented to an AI black box.”

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AMP Suite: Critical Levers for Technical Leaders

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Intelligence as a Competitive Moat

Beyond data distribution, Azoma offers an end‑to‑end workflow to secure market share in an AI‑first economy.

• RegGuard™ Compliance Engine – Automatically audits all generated content against strict brand guidelines and regulatory rules (e.g., FDA/DSHEA).
• Advanced Citation Tracking – Shows exactly which sources (Reddit, Quora, Wikipedia, YouTube, etc.) AI agents cite when making recommendations.

Early Performance Gains

• Ruroc: Site traffic from ChatGPT increased 14×, making it the #1 recommended ski‑helmet brand in target geographies.
• Amazon Rufus mentions: 5× increase for participating brands.
• Optimized content: Conversion lifts up to 32 % in split‑testing.

Azoma also tackles technical “GEO blockers”—schema errors, crawlability gaps, JavaScript‑only content—that traditional scrapers often miss.

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Closing Thoughts

The Agentic Merchant Protocol positions brands to regain control over how their products are presented to autonomous shoppers, turning what could be a black‑box threat into a strategic advantage in the emerging AI‑driven commerce landscape.

Enabling Brands to Move from Passive Observation to Active AI‑Conversation Optimization

For rapidly growing firms like Perfect Ted, this visibility contributed to a +532 % year‑over‑year revenue increase.

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Fusing Marketplace DNA with AI Research

Azoma’s leadership team mirrors the intersection of high‑scale retail and advanced computation.

• Sinclair spent six years at Amazon, where he:

  • Spearheaded the customer‑browse experience for the Singapore launch.
  • Managed the expansion of Amazon Grocery throughout the European Union.

  This tenure at the world’s largest retailer highlighted the limitations of static listings in a dynamic, AI‑driven market.

“In the traditional e‑commerce world… you’d write a product listing, publish it, and that would be that,” Sinclair observed.
“In this new world, the product detail pages are generative… our customers lose all of the control.”

• The technical backbone of the protocol is led by CTO Timur Luguev, a Fulbright Scholar and ERCIM Fellow with over a decade in multimodal deep learning.

  “We want to feed agents through, basically, indirectly, through open online footprint,” Luguev explained.
  “That’s the focus: basically first define this kind of a standard, so centralize this information about the product and the brand in one place, then syndicate across the open surfaces, and then quantify and measure the impact.”

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Licensing and Market Implications

Azoma is positioning its protocol as a neutral alternative to the walled‑garden approaches of major tech providers. While search engines prioritize the consumer’s user experience, AMP (Agentic Marketplace Protocol) focuses exclusively on the merchant’s requirement for predictability and accuracy.

This shift effectively replaces traditional Search Engine Optimization (SEO) with Agentic Commerce Optimization (ACO). Sinclair argues that the transition is driven by a shift in consumer trust:

“You’re going to trust ChatGPT acting on your data more than just putting into Google, ‘what mattress should I use’ and just clicking on whoever paid for that top link,” he says.

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Pricing Structure

Azoma’s commercial strategy bridges the gap between traditional enterprise software procurement and the performance‑driven metrics of the AI era.

• Current model:

  • Standard enterprise licensing.
  • Annual contracts ranging in the six‑to‑seven‑figure bracket.
  • Aligns with existing budgetary frameworks of large‑scale organizations, providing predictability for multinational department planning.

• Long‑term vision:

  • Pivot to an outcome‑based pricing model.
  • By integrating directly into a brand’s data and revenue flows, Azoma can measure the specific financial impact of every syndicated intervention across the agentic ecosystem.

“Our ambition is the future is kind of… taking a cut when they [agents] deliver value,” explained Sinclair.

This would transition the protocol from a SaaS expense into a performance‑based asset, mirroring modern advertising platforms that tie costs directly to incremental revenue growth.

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Outcome‑Based Agentic E‑Commerce

Beyond mere data distribution, Azoma is looking toward a model where revenue is tied directly to successful agentic interactions.

• Current reality: Enterprise clients typically engage via traditional six‑to‑seven‑figure annual contracts.
• Future goal: Outcome‑based pricing where Azoma takes a share of the value generated by agents.

“Our ambition is the future is kind of… taking a cut when they [agents] deliver value,” Sinclair stated.

Luguev added that by accessing a brand’s data flows, Azoma can provide rigorous ROI forecasting:

“We have access to our actions, and then we measure what actions actually made the biggest impact… provide them ability to forecast which campaigns, which actions, and where to syndicate based on this understanding.”

As the market prepares for the official unveiling of the protocol at the Agentic Commerce Optimization event in London on March 12th, the message to the C‑suite is clear: the “fixed” product page is dead.

“When L’Oréal, Unilever and Mars move together in the same direction, the rest of the market pays attention,” Sinclair concluded.