Value Proposition & Features

• Shopping-agent visibility measurement: Tracks how agents see, rank, mention, cite, and recommend products. [2][5]
• Multi-agent monitoring: Covers 10 agents, including ChatGPT, Gemini, Google AI Overviews, Perplexity, Claude, Alexa for Shopping, Walmart Sparky, Instacart Clementine, Lazada Lazzie, and Target Shopping Assistant. [1][9]
• Agentic modules: Generate, approve, and publish listing, website, and third-party content used by shopping agents. [2]
• Product-data optimization: Improves item names, features, descriptions, attributes, variants, rich media, and Q&A. [8]
• Prompt and persona tracking: Measures visibility across selected markets, agents, shopper prompts, and personas. [9]
• Digital Twin technology: Simulates AI shopper personas to show how different buyer types encounter a brand’s products. [3]
• Platform integrations: Connects marketplaces, product-data systems, and analytics supporting a catalog. [2]
• Conversational Briefs: Captures product use cases, buying contexts, and combinations to help agents understand products. [4]

Screenshots

Product Roadmap / Announcements

• October 21, 2026 — Series A announcement: Azoma announced an $11.2 million Series A and said funding would support expansion into personal AI assistants such as ChatGPT Dots and Meta Muse. [3]
• October 2026 — Personal-agent expansion: Azoma described plans to support agents that can build product shortlists and purchase on a shopper’s behalf. [4]
• November 2026 — Changelog: Azoma’s public changelog describes new product updates and features but the available result does not enumerate individual entries. [6]

Recent Developments

• Azoma announced an $11.2 million Series A led by Puma Growth Partners, bringing reported total funding to $15.2 million after the round. [3] ^[F1]
• The company said revenue had grown almost tenfold year over year and that its team had expanded from 12 to 40 employees across London and Toronto. [3]
• Azoma said it holds two granted patents covering AI brand monitoring and AI product-content creation. [3]

History and Origin Story

Fundraising History

{
  "rounds": [
    {
      "id": "azoma:series_a:2026-10-21",
      "url": "https://fireround.dev/companies/azoma",
      "company": {
        "name": "Azoma",
        "domain": "azoma.ai",
        "website": "https://azoma.ai",
        "description": "a leading Agentic Commerce Optimization (ACO) platform that helps brands drive revenue through AI shopping agents",
        "sector": "ai",
        "headquarters": "London and Toronto"
      },
      "stage": "series_a",
      "stage_as_written": "Series A",
      "amount": {
        "usd_millions": 11.2,
        "as_written": "$11.2M",
        "currency": "USD"
      },
      "valuation": null,
      "valuation_disclosed": null,
      "total_as_written": "$15.2M",
      "announced_on": "2026-09-10",
      "date_precision": "day",
      "certainty": "announced",
      "verified": true,
      "provisional": false,
      "earlier_round": true,
      "is_extension": false,
      "lead_investors": [
        "Puma Growth Partners"
      ],
      "other_investors": [
        "Dunnhumby Ventures",
        "Google DeepMind",
        "Ignite Ventures",
        "Legora",
        "MaRS IAF",
        "Rank Ventures",
        "Twin Path"
      ],
      "evidence": "the round led by Puma Growth Partners, with participation from dunnhumby, Twin Path, MaRS IAF, Rank Ventures and Ignite Ventures",
      "primary_source": {
        "url": "https://www.azoma.ai/insights/meta-muse-ai-shopping-agent-azoma-brand-visibility",
        "kind": "company"
      },
      "sources": [
        {
          "url": "https://www.azoma.ai/insights/meta-muse-ai-shopping-agent-azoma-brand-visibility",
          "title": "Meta Muse launches: Azoma on what personal AI agents change for brand visibility",
          "publisher": "azoma.ai",
          "published": "2026-09-10"
        },
        {
          "url": "https://www.azoma.ai/insights/azoma-receives-investment-from-dunnhumby-ventures-to-accelerate-its-agentic-commerce-optimization-platform",
          "title": "Azoma receives investment from dunnhumby ventures to accelerate its Agentic Commerce Optimization platform",
          "publisher": "azoma.ai",
          "published": "2026-09-18"
        },
        {
          "url": "https://www.azoma.ai/insights/azoma-raises-11.2-million-series-a-to-continue-defining-the-agentic-commerce-optimization-category",
          "title": "Azoma raises $11.2 million Series A to continue defining the Agentic Commerce Optimization category",
          "publisher": "azoma.ai",
          "published": "2026-10-21"
        }
      ],
      "source_count": 74,
      "trending": null,
      "previous_rounds": []
    }
  ]
}

Notable Team Members

Market Sizing

Category, Market Size, and Category Growth

Pricing

Revenue Trajectory Estimates

Competitive Landscape

Who it's for, who it's not for

Viable Alternatives

• Traditional enterprise SEO and GEO platforms: Suitable for brands prioritizing web-search and answer-engine visibility rather than retailer-agent execution.
• Product-information-management platforms: Suitable for centralizing catalog data, but generally narrower than Azoma’s agent measurement and recommendation analysis.
• Retail marketplace-optimization tools: Suitable for optimizing listings on individual marketplaces rather than monitoring multiple AI agents.
• In-house analytics and content operations: Suitable for large brands with engineering, commerce, and digital-marketing teams capable of building multi-agent monitoring internally.

Competitor Table

Sources

Sources (retrieved)