Make your agents faster and cheaper.

This demo shows how simple it is to deploy data-driven agents with Infino. We pointed Infino at data sets and it ingested without us defining any schemas, chunking, ETL, etc. other than a data description in a README.md file. In parallel we ingested the same data in Elastic and Snowflake. Once ingested, we run Claude Code as the agent on top of Infino vs. Elastic vs. Snowflake so you can see the same question and agent running side by side. Or you can also point Infino at your own data to see how it performs.

Not only is retrieval faster and cheaper, but so are your agents as they retrieve the right data they need faster, more accurately, and more economically. The results here show your end to end latency and cost, and include what you pay to Anthropic for each query.

Point Infino at a bucket.

pip install infinoquickstart →

Go deeper: playground · hybrid search · docs ↗