Advanced search controls
Set the rules for relevant results. Filters and ranking controls help match each query with the right information.
Fast, accurate product and file search. Offload tuning without losing control. Always in sync with your sources.
Powerful infrastructure for search and ingestion.
Find the right result for each query. Keep ranking and filters aligned with your goals.
Find the right result for each query. Keep ranking and filters aligned with your goals.
Sync information and self-improve search.
Every layer above ships together, on one index. Nothing to wire and nothing to keep aligned.
claude mcp add --transport http captain https://mcp.captain.dev/mcp \ --header "Authorization: Bearer cap_..."
Used by Y Combinator, compliance teams, and engineers building agents that need reliable answers.
The accuracy was noticeably better. Setup took 5 minutes, and it scaled to thousands of docs a day.
View the post on LinkedIn
Garry TanCaptain is a step function increase in capability compared to out-of-box RAG pipelines.
View the post on LinkedInPublic benchmarks are a starting point. What matters is how well search works with your data and the goals you set. Run with Captain’s MCP to measure retrieval and compare changes against your accuracy or latency target.
When evaluated against other leading file-search APIs on production queries, alternatives fail to answer about one in three questions.
See what people search for, and exactly where answers fall short. The feedback loop makes retrieval better over time.
See the questions your data has yet to answer, surfaced automatically, so you know exactly where to close the gaps.
Catch black-hole vector attacks (arXiv:2604.05480) before they reach production, a failure mode most DIY search layers never fix.
Set the rules for relevant results. Filters and ranking controls help match each query with the right information.
Captain’s AI agents identify search problems and test improvements using your business data and search activity. Your team stays in control.
Use your business information to give search the context behind a query. Keep results connected to the goals your team is working toward.
Opt-in PII masking redacts sensitive information when your files are indexed, so it can be hidden from your AI agents.

Our famous file search API.
Point it at your files and search them. Parsing, embeddings, vector DB and evaluation, all managed for you.

Evaluate and tune your file search.
Call captain_eval from the hosted MCP server and it scores retrieval on evals written from your own files, then tunes toward the accuracy or latency target you set.

Bucket change notifications drive the index in near real time, and scheduled reconciliation jobs sweep for anything a notification dropped.
Your buckets remain the source of truth.
Search content inside scanned documents, tables and recordings without building a parsing pipeline.
XML fragments in a zip, with tables that only exist as formatting. Captain's parser was tuned on the ugliest DOCX files our customers could find.
Clean PDFs parse anywhere. Captain also reads the rotated scan and the handwritten margin note.
Transcribed, described and indexed at ingest. The chart on slide 12 is a query, not a scrubbing session.
TLS in transit and encryption at rest protect your data. Opt-in PII masking helps keep sensitive file content out of search results.