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Semantic Caching

A caching technique that returns a stored LLM response when a new query is semantically similar to a past one, rather than requiring an exact text match.

What Is Semantic Caching?

Traditional caching keys on exact strings, so "reset my password" and "how do I reset password" miss each other. Semantic caching embeds the query and checks vector similarity against cached entries, serving the stored answer when similarity passes a threshold. It cuts cost and latency on repetitive queries common in support and FAQ workloads, but needs a tuned threshold so near-misses do not return wrong answers.

How Groovy Web Uses This

We add semantic caching to high-traffic LLM features where repeated questions dominate, cutting token spend while keeping a similarity threshold conservative enough to avoid wrong-answer leaks.

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