Semantic Caching

Semantic Caching converts a question into an embedding and searches a vector database for the most similar previously stored question-and-answer pair, rather than requiring exact string matching. Questions such as “How can I get a refund?” and “Please explain the refund process” can share a cached response despite different wording, reducing API calls. An overly permissive similarity threshold can incorrectly reuse an answer for subtly different requests, such as refunds and exchanges. Precise tuning and recurring cache-quality checks are therefore necessary.

Business applications and impact#

Reduces API costs and response latency in customer-support chatbots and FAQ services that receive repeated questions.

Implementation guidance and considerations#

Tune similarity thresholds and design cache-invalidation policies carefully to avoid incorrect reuse for subtly different requests.