[CMLewis]

Thanks! The largest alternative to Captain is folks trying to build file search themselves. As mentioned in the post, it is a lot to manage.

The most similar product I've seen is Vertex File Search. They're hosted inside of GCP which can fit nicely into existing cloud deployments. Captain indexes from more sources (like R2 for example) and anecdotally provides faster indexing.

[whattheheckheck]

You ought to also look at AWS Kendra GenAI Index + AWS Bedrock retrieve_and_generate().

The cost is insane but its dumb simple

[freakynit]

Hey, congrats on the launch..

How do you compare to kapa.ai ? I have tried them.. and on search quality, they are really impressive.

[jzig]

What about OpenSearch, Onyx, Glean Search, Kore.AI, Sana Labs?

[CMLewis]

OpenSearch provides general search infrastructure and they recently added vector search. It's a low level engine so users would still need to build their own ingestion, parsing, chunking, embeddings, re-ranking, permissions, etc.

Onyx, Sana, and Glean are closer to application-layer enterprise AI products. Their internal knowledge assistants can search across SaaS tools but the interface is more graphical and seats are purchased as end-user software.

Captain sits in between because it's an API-first retrieval system to fully-manage file workloads. This adds search capabilities to existing AI agents but the agents are managed by the developers, outside of Captain.

Kore.ai however is more of an agent platform. Their focus is building and orchestrating agent workflows (which can include document retrieval, but that's not their main focus).