Seltz – The fastest, high quality, search API for AI agents
Hi HN, Antonio here. Founder of Seltz. Seltz is a web search API built for AI agents. We wrote the crawler, the index, and the retrieval models ourselves, in Rust, by a team that's spent years building web search at scale. In our tests, queries come back in under 200ms. Efficiency was the first design principle. Search sits on the critical path: agents can't generate their first tokens or kick off the next tool call until results come back. When you run tens or hundreds of queries in parallel, every millisecond of tail latency compounds. Most search APIs for agents are wrappers around Google…
What it does
In the maker’s words, at launch
Hi HN, Antonio here. Founder of Seltz. Seltz is a web search API built for AI agents. We wrote the crawler, the index, and the retrieval models ourselves, in Rust, by a team that's spent years building web search at scale. In our tests, queries come back in under 200ms. Efficiency was the first design principle. Search sits on the critical path: agents can't generate their first tokens or kick off the next tool call until results come back. When you run tens or hundreds of queries in parallel, every millisecond of tail latency compounds. Most search APIs for agents are wrappers around Google or Bing. If your agent already has a Google tool, a second call to a Google-wrapped API returns the same ten documents. We run our own independent index, so you get different results and different rankings. Coverage starts with US news. More verticals are coming. There's a free tier with $100 in credits at the link. I'd love feedback from anyone building agents: how does it compare to what you're using, and where does it fall over?
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The new Firecrawl /searchJul 2026 · docs.firecrawl.dev · ▲257Our most accurate Search API for AI agents.

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Hey HN! We (Stephan and Thomas) recently open-sourced Semble. We kept running into the same problem while using Claude Code on large codebases: when the agent can't find something directly, it falls back to grep, reading full files or launching subagents. This uses a lot of tokens, and often still misses the relevant code. There are existing tools for this, but they were either too slow to index on demand, needed API keys, or had poor retrieval quality. Semble is our solution for this. It combines static Model2Vec embeddings (using our latest static model: potion-code-16M) with BM25, fused…



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