Azoma, the London platform that helps consumer brands get found and recommended by AI shopping agents, said on Wednesday it has raised an $11.2 million Series A round led by Puma Growth Partners. The company’s official announcement, released through GlobeNewswire on October 21, follows a $4 million seed round announced in December 2025 and will fund expansion across AI personal assistants, deeper optimisation and attribution tooling, and further hiring.
Azoma calls its discipline Agentic Commerce Optimization, or ACO: making a brand’s products discoverable, understandable and recommended when the answer to a shopper’s question is a purchase decision. The round drew participation from dunnhumby, Twin Path, MaRS IAF, Rank Ventures and Ignite Ventures, plus angels from Google DeepMind and Legora.
What Azoma Measures, And Where
Most AI-visibility tools measure general-purpose chatbots. Azoma’s pitch is coverage of the places where purchases actually complete: retailer shopping assistants including Alexa for Shopping, Walmart’s Sparky and Instacart’s Clementine, alongside LLM applications such as ChatGPT and Gemini and personal agents including Meta Muse and ChatGPT Dots. The platform combines measurement, optimisation and execution in one product, and the company says it holds two granted patents covering AI brand monitoring and AI product content creation.
Its Digital Twin feature simulates AI shopper personas, so a brand can see how a particular type of buyer is shown its products rather than relying on a single visibility score. Azoma also co-authored the industry ACO framework — the 5 C’s of Agentic Commerce: Completeness, Context, Citations, Correctness and Customer Acquisition — with the Digital Shelf Institute, and says the framework is deployed in 40% of the 50 largest consumer packaged goods companies.
The Numbers In The Announcement
Azoma says revenue has grown almost tenfold over the past year and its team has expanded from 12 to 40 people. Its named customers are global consumer brands: L’Oréal, Unilever, Mars, Beiersdorf and Reckitt. The announcement also publishes the company’s own citation research: across an analysis of 38 million citations, editorial coverage accounts for 51.9% of what Google Gemini cites but only 7.6% on Google AI Overviews, while affiliate content drives 39.6% of Alexa for Shopping’s citations and under 2% on every other engine measured — a spread the company uses to argue that each agent assembles its answers from different sources, so each needs separate optimisation.
Chief executive and co-founder Max Sinclair, a former Amazon executive, framed the round around speed: agent-to-agent commerce, he said, “has arrived faster than anyone expected.” Puma Growth Partners’ investment director Henri Songeur called Azoma’s measurement product defensible, with enterprise customers already in place. The announcement also cites McKinsey’s projection that agentic commerce could reach $5 trillion globally by 2030, including up to $1 trillion in US retail revenue — a forecast, attributed to McKinsey, not an Azoma figure.
Why It Matters
Azoma’s raise matters because it prices a new layer of the AI-visibility business. The first generation of tools told brands whether ChatGPT mentioned them; Azoma is selling optimisation for assistants that can complete the transaction themselves, where being omitted does not just cost a click but the sale. That the round is led by a growth investor and includes dunnhumby — Tesco’s retail-data arm — suggests the buyers of this category are the same consumer brands and retailers whose shelf space is now being renegotiated inside AI answers. For the wider GEO and AEO industry, a funded specialist in shopping agents raises the bar for generalist trackers that do not cover retailer assistants at all.
Background
Azoma was founded in 2022 by Max Sinclair and Timur Luguev, a machine-learning PhD and postdoctoral researcher. It defined the Agentic Commerce Optimization label for the work it sells and built its early product on brand monitoring inside AI answers, before expanding into optimisation and execution across product data and content. Its seed round closed less than a year before this Series A. Related coverage: what GEO is and how it works, how brands track visibility inside ChatGPT and Gemini answers and OpenAI’s confirmation that ChatGPT’s missing UTM tags were a bug.
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