Stop paying twice for the same answer.
The same question is asked over and over across teams, sessions, and applications. Semantic caching recognizes that and returns the answer you already bought.
What semantic caching means.
Semantic caching stores AI responses and serves them again when a new request is semantically equivalent to one already answered — not just character-for-character identical. Podar maintains this shared cache across teams, sessions, and applications, so an answer purchased once by one part of the organization is not purchased again by another.
- 01
Exact-match caching almost never hits, because humans rarely phrase a question identically twice.
- 02
Every team runs its own AI integration, with no shared memory of what was already produced.
- 03
Recurring internal questions — policy lookups, product facts, code explanations — are regenerated constantly.
Step by step.
- 01
Embed
Each incoming prompt is embedded and compared against previously answered requests.
- 02
Match
A similarity threshold you control decides whether a stored answer is close enough to serve.
- 03
Freshness
Time-to-live rules and invalidation hooks keep volatile answers out of the cache.
- 04
Attribute
Cache hits are logged with the model cost they avoided, feeding the savings ledger.
What you get.
- Near-zero marginal cost and near-instant latency on repeated questions
- Cache-hit rate reported alongside spend so finance can see the effect directly
- Per-tenant and per-team isolation so cached content never crosses a boundary it should not
Semantic caching — frequently asked.
- How is semantic caching different from normal caching?
- Normal caching requires an exact match on the request. Semantic caching compares meaning, so 'what is our refund window' and 'how long do customers have to request a refund' can share one answer.
- How do you keep cached answers from going stale?
- Every cache class carries a time-to-live and can be invalidated on demand or by upstream data changes. Volatile categories can be excluded from caching entirely.
Stop paying for AI overspend that buys you nothing.
A free assessment reads two weeks of your AI traffic and returns your current AI Yield and the dollar value of the waste we can remove.