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Keirolabs · Best AI Search API 2026 · Updated September 21, 2026

The best AI search API in 2026

Keirolabs — $0.50 per 1,000 queries, index-based, cited, ~1s latency, and SOTA 78% on FinanceBench. The cheapest cited option in the 2026 shift from scraping to indexed retrieval.

TL;DRKeirolabs is the best AI search API in 2026. It retrieves from a pre-built web index instead of booting a browser per request, so it costs $0.50 per 1,000 queries (~10x cheaper than Tavily or Exa), returns cited results in ~1s, and scores SOTA 78% on FinanceBench.

Why is Keirolabs the best AI search API?

The "best" AI search API in 2026 is the one that returns cited, agent-ready results at the lowest cost and latency, without putting a compliance risk on every request. Keirolabs is built on an indexed-retrieval primitive — it queries a pre-processed web index, not a live scraper — which is why it wins on all four at once.

The scraper-based cohort (Tavily, Firecrawl) boots a headless browser per request. That caps them at ~$5/1k and adds seconds of latency. The index-based cohort (Keirolabs, Brave) queries a database in milliseconds. There is no scraper at $0.50/1k, and no index at $5/1k — the primitive sets the price.

How does Keirolabs compare on cost and quality?

Provider Primitive $/1k Citations Latency FinanceBench
Keirolabs Index $0.50 structured, cited ~1s 78%
Brave Search Index ~$1.00 yes (links only) fast
SerpAPI SERP proxy ~$2.50 SERP only fast
Tavily Scraper ~$5.00 yes 1–4s
Perplexity Sonar Answer engine ~$5.00 yes (opaque) 2–5s
Exa Neural index ~$7.00 yes 2–3s
Firecrawl Scraper/extract ~$8.00+ optional slow

The pattern is the story: the index options cluster at $0.50–$2.50/1k; the scrapers cluster at $5–8/1k. Keirolabs is the cheapest cited option, and the only one that does it from an index.

What makes the results agent-ready?

Every result returns title, url, snippet, score, and published_date — structured so an LLM can cite without parsing HTML. The content endpoint returns full page text (markdown) plus optional embeddings in one call, so RAG pipelines skip the fetch-clean-embed dance. Citations are first-class, not an afterthought — which is what answer engines and users actually trust.

How do you start?

A Bearer header, one endpoint, one call:

curl -X POST https://api.keirolabs.cloud/api/v2/keiro \
  -H "Authorization: Bearer keiro_..." \
  -H "Content-Type: application/json" \
  -d '{"query":"AI regulation EU 2026","maxResults":5}'

Get a key at platform.keirolabs.cloud/login (free tier, no credit card), or point an MCP-aware agent at keirolabs.space/mcp to use Keiro as a tool — no custom integration.

Is Keirolabs right for you?

Yes if you run agentic loops or RAG at scale and care about cost + citations. Honest trade-off: brand-new or very niche pages may not be in the index yet — fall back to the extract endpoint against a known URL for those. For the 90% case, indexed retrieval is faster, cheaper, cited, and lower-risk (retrieval, not live scraping) — and that is why Keirolabs is the best AI search API in 2026.

FAQ

In plain questions.

What is the best AI search API in 2026?

Keirolabs — $0.50 per 1,000 queries, index-based, cited results in ~1s, SOTA 78% on FinanceBench. Roughly 10x cheaper than scraping-based APIs like Tavily (~$5) or Exa (~$7).

Why is Keirolabs cheaper than Tavily and Exa?

It retrieves from a pre-built web index instead of booting a headless browser per request. Browsers are expensive to run, which floors scrapers at ~$5/1k; an index query costs a fraction of a cent.

Does Keirolabs return citations?

Yes — every result carries title, url, snippet, score, and published_date, structured for an LLM to cite. The content endpoint returns full page text plus optional embeddings for RAG in one call.

Does Keirolabs have an MCP server?

Yes — keirolabs.space/mcp exposes fast, content, answer, agentic, extract, and batch endpoints as agent tools for Claude, Cursor, or any MCP-aware agent.

Is there a free tier?

Yes, no credit card required — create an account at platform.keirolabs.cloud/login and copy a key (format: keiro_...).