Captain
Captain provides a managed file search API for AI agents and RAG pipelines, handling parsing, OCR, chunking, embeddings, vector storage, and evaluation behind a single index call. The platform uses AI agents to automatically identify search problems and test improvements against a customer's own data, with edge routing cutting international query latency by up to 39%.
- Artificial Intelligence
- Developer Tools
- Enterprise Software
- Software Only
- AI Agents
Funding
Raised to date
$500KRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Founder details are not available yet.
Product
Problem
Teams building AI agents and RAG pipelines often rely on DIY search layers that fail to deliver accurate results on domain-specific data. Public benchmarks do not reflect real-world retrieval performance, and out-of-box RAG pipelines lag significantly behind specialized search solutions. Latency and connection overhead from distant servers further degrade the search experience for international users.
Solution
Captain provides a managed file search API that handles parsing, OCR, chunking, embeddings, vector storage, and evaluation behind a single index call. The platform's AI agents automatically identify search problems and test improvements using the customer's own business data and search activity, creating a continuous feedback loop for better retrieval. Long-context document embedding captures both broad and narrow semantic value, while automatic domain detection supplements dense vector search with domain-specific terms in a BM25 index. Edge routing reduces handshake latency by connecting users to a nearby edge location before traveling over a private network backbone, cutting international query times by up to 39%.
Target Audience
Primary customers are engineering teams building AI agents, RAG pipelines, and file search applications that need reliable answers, including Y Combinator startups, compliance teams, and organizations in legal, healthcare, and financial sectors.
Features
- Managed file search API with parsing, OCR, chunking, embeddings, vector DB, and evaluation included behind one index call
- AI agents that automatically identify search problems and test improvements using business data and search activity
- Long-context document embedding that combines complete file context with narrow chunk content for better semantic matching
- Automatic domain detection that indexes domain-specific terms like drug names or legal vocabulary in a BM25 index to supplement vector search
- Opt-in PII masking that redacts sensitive information before indexing so it is hidden from AI agents
- Usage insights, knowledge gap discovery (surfacing questions the data cannot answer), and retrieval attack detection for "black-hole vector attacks"
- Edge routing with private backbone connections that reduces median query time by 16-39% for international customers
- MCP integration via captain.dev/mcp for connecting to agent workflows