FAQs 

Ceramic.ai Search is a lexical search API built for LLMs and AI agents, returning relevant, high-quality content for keyword queries. Unlike traditional consumer search engines, Ceramic.ai is designed specifically to plug into AI agent workflows and LLM tool-calling pipelines.

Lexical search matches queries against the actual words in a document, using exact terms, synonyms, and keyword variants, while semantic search relies on vector embeddings to infer meaning and intent. Both have real tradeoffs:

• Lexical search advantages: transparent and debuggable results (you can see exactly why something matched), lower latency and infrastructure cost at scale, no embedding model to retrain or version, and strong performance on named entities, technical terms, and fresh content.
• Lexical search disadvantages: doesn't natively understand paraphrasing or vague intent, so queries need to be rewritten into precise keywords for best results.
• Semantic search advantages: handles conversational or vague queries well, can match concepts even with no shared vocabulary.
• Semantic search disadvantages: embedding models need retraining to stay current, results are harder to explain, cost and latency scale with vector index size.

Ceramic.ai chose lexical search because our core use case, LLMs and AI agents doing tool-calling, already produces precise keyword queries (often via a rewriting step), so we optimize for speed, freshness, and explainability instead of paying the latency and cost tax of semantic inference on every call.

Compared to semantic-first search APIs on the market, lexical search avoids a known failure mode: because semantic engines match on meaning rather than exact terms, they can return results that are conceptually related but not actually relevant to what the user asked, a tradeoff that matters most in agentic workflows where one bad result silently derails the next step in a chain. Lexical search's transparency (you can always see why a result matched) and lower compute overhead also feed directly into Ceramic.ai's pricing advantage.

Ceramic.ai Search pricing starts at $0.05 per 1,000 queries on the Pay As You Go plan, well below typical market rates for AI search APIs, which generally range from $0.30 to $10+ per 1,000 queries with Pro and Enterprise plans available for higher-volume or custom needs. See the pricing page for full details.

You can call the Ceramic.ai Search API directly, use our SDK, or connect through the Ceramic.ai MCP server, and see the quickstart docs for setup instructions. Because Ceramic.ai is a lexical, not semantic, search engine, we recommend reading the best practices guide for techniques like query rewriting and using multiple keyword variants to get the most relevant results.

Ceramic.ai integrates directly via our MCP server and supports popular AI agent frameworks including LangChain, OpenClaw, and CrewAI. See the integrations docs for the full list.

Yes, Ceramic.ai is a launch partner for Cloudflare's Pay Per Use program, which compensates publishers when their content is returned in our search results.

Ceramic.ai has built its own 40B+ page web index through direct publisher partnerships and legal crawling, not scraping.

Yes, Ceramic.ai has completed both SOC 2 Type I and Type II audits. See our Trust Center for compliance details and controls. Full audit reports are available to enterprise prospects under NDA.

The AI search API market has split into two camps: scraper-based tools that boot a headless browser per query, reading and cleaning raw HTML in real time, and index-based APIs like Ceramic.ai that retrieve directly from a pre-built index. Scraping is slower, more expensive at scale, and faces growing legal scrutiny; index-based retrieval is faster and cheaper because the heavy lifting happens ahead of time, not on every request. Ceramic.ai's 40B+ page index was built through direct publisher partnerships and legal crawling, not scraping, which is also what makes publisher compensation possible and something scraper-based tools don't offer.

Yes, Ceramic.ai offers 1,000 free queries on our web search to get you started, so you can test integration and result quality before committing to a paid plan.

Ceramic.ai was founded by Anna Patterson, a former Google Search architect, and is backed by a $12M seed round led by NEA. Read more about Ceramic.ai's funding and origin story (TechCrunch). Ceramic.ai's focus has evolved from AI training infrastructure to search since its inception. The team brings deep search infrastructure experience, with a mission of helping AI agents and LLMs get more relevant, verifiable results than general-purpose consumer search APIs provide.