Azoma
Azoma is a generative engine optimization platform built specifically for ecommerce. It evaluates product pages and product data at the SKU level, flagging the issues that keep AI shopping assistants from surfacing a product - schema problems, crawlability gaps, JS-only content, and thin titles, images, variants and attributes - and then fills those gaps to improve how large language models understand and cite the product. It produces analytics and content tuned for AI shopping surfaces such as Amazon's Rufus and Walmart's Sparky, and works with consumer brands including Colgate, L'Oreal, Unilever, P&G, HP and Reckitt. In 2026 it introduced a '5 C's of Agentic Commerce' framework adopted by several large CPG companies.
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Our take
Azoma is GEO built specifically for ecommerce: it audits product pages at SKU level for the things that stop AI shopping assistants from surfacing them - schema gaps, crawlability, thin attributes - then fills those gaps so models like Amazon's Rufus and Walmart's Sparky can read and cite them. Blue-chip CPG logos and an enterprise focus mean contact-sales pricing.
Best for
Consumer brands and retailers that need their products discovered and accurately described by AI shopping assistants, and want SKU-level audits rather than generic AI-visibility dashboards.
Pros
- Vertical focus on ecommerce, not generic GEO
- SKU-level audits of product data and schema
- Targets AI shopping surfaces like Rufus and Sparky
- Used by major CPG brands
Cons
- Enterprise pricing, not self-serve
- Best fit for brands with large catalogs
- Young category with evolving AI-shopping surfaces
How it compares
Against broad AI-visibility tools like Profound or Peec, Azoma is commerce-specific and works at the SKU and product-feed level rather than tracking brand mentions.
Full review
Azoma is a generative engine optimization platform built specifically for ecommerce. It evaluates product pages and product data at the SKU level, flagging the issues that keep AI shopping assistants from surfacing a product - schema problems, crawlability gaps, JS-only content, and thin titles, images, variants and attributes - and then fills those gaps to improve how large language models understand and cite the product. It produces analytics and content tuned for AI shopping surfaces such as Amazon's Rufus and Walmart's Sparky, and works with consumer brands including Colgate, L'Oreal, Unilever, P&G, HP and Reckitt. In 2026 it introduced a '5 C's of Agentic Commerce' framework adopted by several large CPG companies.
Against broad AI-visibility tools like Profound or Peec, Azoma is commerce-specific and works at the SKU and product-feed level rather than tracking brand mentions.
Cloudkart Trust Graph
3.8/5- Actual Utility4/5
Source: Initial LLM-authored rubric (backfill)
- Ease of Use3/5
Source: Initial LLM-authored rubric (backfill)
- Pricing Fairness3/5
Source: Initial LLM-authored rubric (backfill)
- Reliability4/5
Source: Initial LLM-authored rubric (backfill)
- Differentiation5/5
Source: Initial LLM-authored rubric (backfill)
Scored as of . Each score is versioned and auditable; vendors cannot buy it.
How this score is set
- Editorial rubric
- Primary signal — five dimensions, 3.8/5 average.
- Community reviews
- None yet.
- Pricing verified
- Not yet verified
- Independence
- Score set by our editorial team before any affiliate relationship is considered. No vendor can buy it.
Frequently asked questions
- Is Azoma free, and how much does it cost?
- Azoma is a paid tool.
- Who is Azoma best for?
- Consumer brands and retailers that need their products discovered and accurately described by AI shopping assistants, and want SKU-level audits rather than generic AI-visibility dashboards.
- How is Azoma rated on Cloudkart.ai?
- Azoma scores 3.8 out of 5 on the Cloudkart.ai rubric, which weighs actual utility, ease of use, pricing fairness, reliability and differentiation. Scores are set editorially and can never be bought.
Community reviews
No community reviews yet. Be the first to share how Azoma works for you.
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Phia
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Rep AI
Behavioral AI sales agent for Shopify that engages shoppers, recommends products and drives checkout — trained on 160M+ shopper sessions.
Compare Azoma head-to-head: vs Stripe Agentic Commerce · vs Stripe Agent Toolkit · vs Phia · vs Rep AI