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Captain

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Give AI agents accurate knowledge search that scales

Winter 2026Founded 20252 peopleSan Francisco, CA, USA
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AI insightcan contain mistakes
AI Agent Search & RAGAPI/InfraAI teams and enterprisesHigh competition
Moat
Superior accuracy (20% above standard RAG) and petabyte-scale multimodal search capability.
Key risk
Embedding model providers may integrate superior search; commoditization risk as RAG matures.
Why now
Enterprise AI agents are being deployed; search accuracy is critical bottleneck.
Competitors
Weaviate, Pinecone, Vespa

About

Captain delivers the most accurate file search engine built for AI agents. We’ll index data from the sources folks already use like S3, SharePoint, and Google Drive, and easily scale multimodal, petabyte-level content search. We’re the Snowflake for Unstructured Data. Captain tops the Open-RAG-Benchmark with over 20% higher accuracy than standard RAG pipelines. We achieve this through robust data processing techniques like embedding normalization across modalities, ensuring that representations cluster by semantic content rather than data type.

Founders · 2

Lewis Polansky
Lewis PolanskyCEO/Co-Founder

CEO @ Captain, Prev. IEEE, Founded CyberSpace (CTF hacking group), Recognized by the U.S. Congress for leadership in community software projects, Avid designer, Dropped out of Purdue

Edgar Babajanyan
Edgar BabajanyanCo-Founder and CTO

CTO @ Captain | Published AI NLP Researcher | Built OCR engines @ Boar's Head | Scaled high-performance RAG pipelines for the past 4 years | Built a Cross Region L2 Datacenter

B2BInfrastructureB2BAPIData EngineeringInfrastructure

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