For future-focused e-commerce brands, the primary customer is increasingly changing from the person behind the screen to AI agents, who said human customers are positioned to research on their behalf and, if projections are correct, purchase products on their behalf.
For example, investment banking and financial services giant Morgan Stanley has published research suggesting that agents could account for 10-20% of all U.S. commerce spending by 2030 – ranging from $190 billion to $385 billion.
In response to this seismic shift, four-year-old agentic AI e-commerce startup Azoma has unveiled the Agentic Merchant Protocol (AMP).
This new framework is designed to provide high-volume retailers – such as grocery brands, electronics manufacturers and fashion labels – "brand friendly" Anchoring in an ecosystem dominated by autonomous buyers
The idea is compelling and deceptively simple at its core: Instead of the current status quo in which merchants selling physical products online have to manually enter information about each product, such as SKUs and ingredients, into separate online marketplaces and product listing aggregators (like Walmart, Amazon, Google Shopping, etc.) – brands can now simply take all that information, put it into Azoma’s platform, and take it everywhere, including for users to find and retrieve the information. It also includes optimized pages for AI agents to recommend products that best suit their specific queries.
Using early agentic AI technology to end the ‘black box’ era of e-commerce
Modern AI integration typically relies on siled systems like OpenAI’s ACP or Google’s UCP. While these protocols manage the technical handshake required for discovery and payments, they provide minimal oversight with respect to brand integrity.
When an AI agent is deployed by a customer "Reason" Regarding its human consumer’s product queries, it often synthesizes data from unverified corners of the web, such as Reddit or old affiliate sites, creating a "black box" Impact where the intended message of the brand gets lost.
AMP acts as a high level "system of record" Which bridges these disparate platforms. It allows companies to centralize their product intelligence, including legal guardrails and brand books, into a single, machine-native format.
"AMP breaks the foundation of traditional ecommerce," said Max Sinclair, CEO of Azoma, in a press release shared with VentureBeat ahead of the official announcement taking place on March 12 in London."For decades, marketplaces like Amazon and Walmart acted as gatekeepers by controlling product detail pages, ranking, and distribution. Brands optimized a limited set of endpoints: PDP, ads, search results. In the agentic world, those certain pages no longer exist".
The Azoma platform is specifically designed for high-volume retailers and physical goods manufacturers, with a primary focus on the consumer packaged goods (CPG) and fast-moving consumer goods (FMCG) sectors.
In an interview with VentureBeat, Sinclair clearly distinguished the protocol’s utility from digital-only assets or services, noting that Azoma does not currently support NFTs, SaaS, or financial sectors like banking and insurance.
Whether facilitating automated reordering of household items such as dishwasher soap or providing "logic" Data for high-consideration purchases like specialty supplements and ski hardware, the protocol acts as digital connective tissue for brands whose value lies in the physical world.
Sovereignty in a multi-agent world
The protocol has already been rapidly adopted by a coalition of consumer goods giants including L’Oréal, Unilever, Mars, Beiersdorf and Reckitt. For these organizations, maintaining consistent identity across different AI surfaces is an immediate priority.
"The fact that businesses like L’Oreal, Unilever, Mars and Beiersdorf have moved so quickly to adopt AMP tells you everything about their urgency," Sinclair made the comments during a recent interview with VentureBeat. "These are companies that have spent decades building brand equity – they’re just not taking control of how their products are presented into an AI black box.".
The AMP Suite provides several important levers for tech leaders:
- Canonical Machine-Native Catalog: Data structures designed specifically for LLM ingestion, enriched with personality-level signaling.
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Programmatic Open Web Delivery: Ensuring that data found by agents on the open web matches the brand’s official documentation.
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Agent-agnostic infrastructure: A design that prevents seller lock-in by allowing brands to interface with any AI assistant or marketplace agent.
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display visibility: instrument for measuring agents "weigh" Verify specific product features and compliance across the ecosystem.
Intelligence as a competitive moat
Beyond simple data delivery, Azoma offers an end-to-end workflow designed to secure market share in an AI-first economy.
The platform includes a proprietary "RegGuard™ Compliance" Engine that automatically audits all generated content against strict brand guidelines and regulatory rules such as FDA/DSHEA standards.
This automated inspection is paired with advanced citation tracking, allowing brands to see which sources AI agents are citing when they make a recommendation, from Reddit and Quora to Wikipedia and YouTube.
This expanded visibility has already delivered significant performance benefits for early partners. The company reports that for the Rurok brandSite traffic from ChatGPT has increased 14 times, They are ranked as the #1 recommended ski helmet brand in the targeted geographic areas.
Similarly, customers have seen a 5x increase in the share of their mentions within specific retail agents like Amazon Rufus, while optimized content has demonstrated up to a 32% conversion increase in split-testing.
by addressing technical "GEO Blocker"—such as schema errors, crawlability gaps, and JavaScript-only content that traditional scrapers may miss—Azoma enables brands to transition from passive observation of AI conversations to active optimization.
For fast-growing companies like Perfect Ted, this visibility contributed to +532% year-over-year revenue growth.
Linking market DNA with AI research
Azoma’s leadership team reflects the intersection of high-end retail and advanced computing.
Sinclair spent six years at Amazon, where he led the customer browse experience for the Singapore launch and managed the expansion of Amazon Grocery across the EU.
This stint by 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’s it," Sinclair looked. "In this new world, product detail pages are generative…our customers lose all control".
The technical backbone of the protocol is led by CTO Timur Lugaev, a Fulbright Scholar and ERCIM Fellow with over a decade in multimodal deep learning.
Lugwave sees AMP as a way to indirectly influence the broader "online footprint" Which informs AI logic. "We want to basically, indirectly, feed agents through an open online footprint," Lugwave explained.
"This is the focus: basically define this kind of standard first, so centralize this information about the product and brand in one place, then syndicate across open surfaces, and then measure and measure the impact.".
Licensing and market implications
Azoma is positioning its protocol as a neutral alternative to the walled-off approach of major technology providers. While search engines prioritize the consumer’s user experience, AMP focuses specifically on the merchant’s need for predictability and accuracy.
| Speciality |
Platform Protocol (ACP/UCP) |
Azoma AMP |
|
primary focus |
transaction execution |
Brand Control and Multi-Agent Syndication |
|
data access |
internal ecosystem only |
Cross-platform and open web |
|
brand governance |
No/Partial Inspection |
Full enterprise-defined control |
|
integration |
Developer-centric API |
Marketing and commerce team friendly |
This change effectively replaces traditional search engine optimization (SEO) with agentic commerce optimization (ACO).
Sinclair argues that this change is driven by a change in consumer confidence. "You will trust ChatGPT with your data [more] Instead of just putting ‘what mattress should I use’ into Google and clicking on whoever paid for that top link," He says.
pricing structure
Azoma’s business strategy is designed to bridge the gap between traditional enterprise software purchasing and the performance-driven metrics of the AI age. Currently, the company uses a standard enterprise model, engaging with its global partners through annual contracts that typically fall within the six to seven figure range. This structure is intended to align with the existing budgetary structures of large-scale organisations, providing the predictability needed for multi-national department planning.
However, the company’s long-term vision includes a fundamental pivot toward an outcome-based pricing model. By directly integrating a brand’s data and revenue streams, Azoma can measure the specific financial impact of each syndicated intervention across the agentive ecosystem.
"Our ambition is that the future is kind of… when they cut [agents] provide value," Sinclair explained.
This goal will effectively transform the protocol from a SaaS expense to a performance-based asset, reflecting how modern advertising platforms operate by tying costs directly to incremental revenue growth.
Results-Based Agentic E-Commerce
As the market prepares for the protocol’s official unveiling at the Agentic Commerce Optimization event in London on March 12, the message to the C-suite is clear: "fixed" Product page is dead. "When L’Oréal, Unilever and Mars move together in the same direction, the rest of the market takes notice," Sinclair concluded.
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