Launch HN: Captain (YC W26) – Automated RAG for Files
YC-backed Captain ships enterprise-grade RAG pipelines in minutes with 95% accuracy, eliminating months of manual work.
Captain, a Y Combinator W26 startup, has launched an automated platform for building Retrieval-Augmented Generation (RAG) pipelines. The system promises a dramatic leap in accuracy, moving from an industry average of 78% to 95% for document-based question answering. This is achieved through a fully-managed pipeline that automates the entire workflow: universal indexing with auto-OCR and vision-language models, intelligent chunking, best-in-class embeddings, managed vector storage, and agentic hybrid search. The platform is designed for enterprise deployment, featuring SOC 2 certification and role-based access controls to secure sensitive data.
Unlike manual RAG development, which can take engineering teams 3-6 months to build and maintain, Captain claims users can ship a production-ready system in minutes. The service connects to a wide array of data sources including cloud storage (Amazon S3, GCP, Azure), collaboration tools (SharePoint, Slack, Confluence, Notion), and drives (Google Drive, Dropbox). Developers interact with it through an API-first interface, querying indexed collections of documents with support for streaming, re-ranking, and inference. The company, founded by engineers from Granular, aims to eliminate the 'spotty' performance of custom-built RAG systems by providing a standardized, high-accuracy alternative.
- Boosts RAG accuracy from an average of 78% to 95% through automated, managed pipelines
- Reduces deployment time from 3-6 months of manual engineering to minutes with an API-first platform
- Offers enterprise security with SOC 2 certification and role-based access governance for data collections
Why It Matters
Dramatically reduces the time and expertise required to build reliable, secure AI agents that can answer questions from company documents.