My Claude API Bill Was Growing Fast — Here’s How I Cut It With Semantic Caching

1. 1Build a semantic caching layer using Voyage AI embeddings and Supabase's pgvector extension
2. 2Intercept near-duplicate queries before they hit the LLM
3. 3Implement a caching mechanism to store and retrieve query results
4. 4Optimize the caching layer for performance and accuracy
5. 5Monitor and adjust the caching layer as needed

Developers and engineers working with LLMs and RAG can benefit from this technique to optimize costs and improve performance

💡 Semantic caching can significantly reduce LLM API costs by intercepting near-duplicate queries

Cut your LLM API bill with semantic caching! Learn how to reduce repeated queries and improve performance