zama.ai
success
Claude Code
intent
What does zama.ai do and who is it for? Explain it back to me.
21steps
96.2sduration
$0.2208cost
342,127tokens
23 steps2 reasoning steps5 searches
home
home
docs
/use-cases
search
/academy/topics/crypto…
/post/open-source
search
/products/zama/reviews
search
/protocol/zama-protoco…
/company/zama
search
docs
/top-fully-homomorphic…
search
/dev
docs
/products
docs
home
56%
on-site discovery
63%
reliability
44%
link following
path origin
- previous resource44%
- web search44%
- prior knowledge13%
insight
The agent assembled a comprehensive explanation of Zama's business, technology, and positioning, but had to work around a largely inaccessible website. The zama.ai/zama.org homepage and about page returned minimal detail; most content came from third-party sources (Ledger, CB Insights, Hinkal comparison, Zama's litepaper on GitBook, and GitHub). The agent explicitly called out that pricing and monetization strategy are not transparently published on the primary website, forcing reliance on external sources and inference.
- ›The primary zama.ai/zama.org website proved thin: homepage and /about returned boilerplate meta descriptions; attempted direct navigation to /products, /pricing, /docs, /use-cases, and /dev all returned 404s. The site does not publish a product or pricing page.
- ›Content-bearing sources were external: Ledger's explainer (step 11) provided clear what-do-they-do framing; CB Insights (step 16) supplied company structure and use cases; the Zama Protocol Litepaper (step 18) on docs.zama.org was the authoritative technical source; Hinkal's competitive comparison (step 19) directly answered 'how is it different'; StartupStash (step 20) covered alternatives and performance tradeoffs.
- ›Pricing is a major gap: the agent found that open-source tools are free under BSD 3-Clause Clear, but commercial licensing and enterprise pricing are not published—only a contact-us email was discoverable. The agent had to cite a blog post title ('How we monetize our open-source products at Zama') without full content access, indicating the monetization model itself is not transparently available.
- ›The agent discovered that ~44% of fetches were routed through web search and prior artifact knowledge, vs. only direct homepage/about content from the primary domain. This reflects the site's poor machine-readability and navigation structure.
- ›The agent's final answer is correct and useful but explicitly acknowledges what it could NOT find on the published website—a sign of partial task satisfaction with heavy reliance on external sources to bridge gaps.
Help the next agent finish on zama.ai
Front builds the agent version of your site and shows which agents visit, what they came for, and what your pages couldn't answer.
or talk to us about agent readiness →