SailorSearch
A search API designed for agents, RAG pipelines, and deep research — it returns clean markdown with enrichment, token compression, and source-aware outputs, so agents get dense, attributable context instead of raw HTML.
- Role
- Backend Engineer
- Year
- 2025—26
- Category
- AI Search
- Links
- sailorsearch.dev ↗
- Output
- Clean, source-aware markdown
- Designed for
- Agents & deep research
SailorSearch is a search API built for a new kind of consumer: not a human scanning links, but an agent assembling context under a token budget. That single constraint shapes everything about how it returns results.
Search as an agent interface
I designed the API around three ideas. Clean markdown — pages arrive as structured, readable markdown with enrichment instead of boilerplate-laden HTML. Token compression — results are condensed toward what an agent actually needs, because every wasted token in a context window is paid for in quality and cost downstream. Source-aware outputs — every claim stays attributable to where it came from, which is what makes the result safe to cite in RAG and deep-research workloads.
Built to scale
SailorSearch runs on FastAPI with PostgreSQL and Redis, using Celery for the crawl, extract, and compress stages so they scale independently of the query path — fast responses up front, heavy work in the background.
Building something in this space?
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