Semantic caching stores AI responses keyed by meaning rather than exact text: when a new query is semantically close to a cached one, the system returns the cac
Storing AI responses keyed by meaning rather than exact text: when a new query is semantically close to a cached one, the system returns the cached answer instead of paying for fresh inference.
Staleness and precision. Cache entries need expiry, and 'close enough' similarity thresholds need tuning against wrong-answer risk. For high-traffic assistants where users phrase the same questions endlessly, it cuts cost and latency dramatically.