• •Software engineer Guglielmo Cerri launched Khazad, an open-source library that uses Redis vector sets to cache LLM queries.
• •The tool performs semantic searches to identify and serve cached responses, aiming to reduce API latency and infrastructure costs.
• •The software is currently in its initial release phase; its performance benchmarks against standard string-match caching solutions remain unverified by third parties.

Guglielmo Cerri has released Khazad, an open-source library designed to cache LLM calls using Redis vector search. While traditional caching relies on exact string matches, this tool leverages semantic similarity to identify if a query has been previously answered. However, the performance overhead of performing a vector search for every request remains a primary concern for high-traffic environments. Its long-term utility will depend on how efficiently it handles large datasets compared to simpler key-value caching methods.