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Azoma launches new merchant-side standard for ‘brand friendly’ agentic commerce

Azoma, the pioneers of Agentic Commerce Optimization, today launched Agentic Merchant Protocol (AMP), the powerful new foundational platform empowering retailers and brands to retain control of their ...

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L’Oreal, Unilever, Mars & Beiersdorf first to take back control of AI Visibility

LONDON & TORONTO: Azoma, the pioneers of Agentic Commerce Optimization, today launched Agentic Merchant Protocol (AMP), the powerful new foundational platform empowering retailers and brands to retain control of their product catalogues. Early adopters include some of the world's most recognisable consumer brands and brand owners, such as Mars, L'Oréal, Unilever, Beiersdorf and Reckitt.

Adopting AMP gives early adopters, including major grocery brands, retailers and electronics manufacturers, the ability to differentiate their offers and avoid lock-in to AI providers.

Agentic commerce has crossed a tipping point. On Black Friday 2025 AI chatbots and agents drove an estimated $14.2B in sales globally, over $3B in the U.S. alone. Consumers no longer browse static product pages. Increasingly, they ask agents questions, compare options and evaluate synthesized product recommendations. In effect, machines help them decide what to buy.

Brand representation cannot be left to chance

Platform-specific protocols, like OpenAI ACP and Google’s UCP, quickly connect product data to buyer discovery and checkout workflows. They do not guarantee how brands are represented. The risk is that ‘black boxes’ weigh product data incorrectly, or ignore contradictory information elsewhere online to present offerings out of the context which the seller intended. Even after brands push their information through these channels, AI agents will still form responses by drawing from data across the wider web - sources entirely outside the brand's control.

Just as brands once had to go beyond a single retailer and ensure their product information was accurate everywhere it appeared online, they now need a way to distribute and orchestrate their brand intelligence across the entire agentic ecosystem. That is what AMP delivers.

Max Sinclair, CEO of Azoma commented: “AMP breaks the foundations of traditional ecommerce. 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.”

He added, "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. 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."

The savvy merchant’s choice

OpenAI and Google are racing to establish the consumer agent of choice for commerce. Merchants lack a neutral, enterprise-grade system focused on their needs. Brand control, consistency, compliance and predictability vary across all agentic surfaces. Azoma takes the opposite approach by focusing on merchant needs rather than consumer experiences.

Sinclair added, “AMP radically improves the AI visibility of product information, guaranteeing agents will weigh it correctly. For enterprise brands, this is an existential change. They can now retain control over channels, messaging, accuracy and compliance. Their products are now represented by whatever information agents find and synthesize, often from unverified or outdated sources.“

The missing layer in agentic commerce - how AMP works

  • Canonical, machine-native product catalogues
    Enriched with brand guidelines, compliance guardrails, target personas, competitive context, and availability rules
  • Programmatic Open Web distribution
    Co-ordinated across the open web and agent ecosystems to ensure relevant product knowledge surfaces where agents reason and decide
  • Contextual prioritization of content
    Information distribution guided by persona-level signals to determine which buyer questions and answers matter, which product attributes and content to refresh
  • Agent-agnostic interface
    Interchangeable chat-based agents and marketplace assistants to reduce dependence on any one platform’s incentives or roadmap.

Independent enterprise-first brand amplification

Azoma’s Agentic Merchant Protocol is an independent, enterprise-first protocol that gives brands and retailers a single system to define how their product catalogues are understood, reasoned over, and acted upon by machines across every AI agent and the broader online sources that inform from. Azoma does not replace ACP or UCP. It sits above them.

The Azoma protocol allows merchants to feed catalogue product intelligence once, handling distribution everywhere, including agent platforms via ACP and UCP and by shaping the broader online footprint. With this move, Azoma is laying out its plans to become the system of record for agentic commerce. Enterprises define their product catalogues, brand guidelines, regulatory and compliance requirements, and the protocol ensures this intelligence is syndicated across the agentic ecosystem.

​​"We're proud to be working with some of Britain and Europe's most iconic consumer brands from day one," added Sinclair. "When L'Oréal, Unilever and Mars move together in the same direction, the rest of the market pays attention."

FOR EDITORS

Agentic Commerce Protocols: Comparative View

Dimension

OpenAI ACP

Google UCP

Azoma Agentic Merchant Protocol

Primary focus

Agent execution & checkout

Consumer discovery & checkout

Brand representation control, analytics, attribution & multi-agent syndication

Structured product data feed

Yes

Yes

Yes

Focus on agent-driven checkout

Yes

Yes

No

Cross-agent syndication

No

Partial (across Google agents only)

Yes (across agents & open web)

Brand & product representation control

No

Partial (within Google experiences)

Yes (enterprise-defined, cross-surface)

Agentic content orchestration

No

Limited orchestration inside Google’s ecosystem

Yes (data-driven, cross-surface)

Performance analytics (agentic visibility)

No

Partial (Google surfaces only)

Yes

Attribution & ROI forecasting

No

No

Yes

Onboarding orientation

Developer APIs

Developer tools

Whiteglove for marketing & commerce teams

 

Fonte: Business Wire

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