Stop Paying the Provider Twice for the Same Answer

Govern access before spend happens

Repeated, identical requests — the same support macro, the same classification prompt, the same tool-call pattern — are common in production LLM traffic, but most teams have no safe way to short-circuit them. Turning caching on blind risks serving one customer's cached response to another, or caching something that should never repeat. Teams need cache scope, safety, and savings to be provable before enforcement is switched on.

• Duplicate requests billed to the provider every time
• No safe way to scope a cache without leaking across tenants, apps, or environments
• Enforcing cache blind risks a stale answer served with no visibility
• No way to know the savings before committing to enforcement

One policy layer across model usage

Cloptima fingerprints eligible requests within a policy-defined namespace — tenant, app, model, environment, and any other key-scope dimensions your policy declares — then checks a Redis-backed exact match before the provider is called. Observe mode logs cache-eligible hits without serving them, so you see hit rate and dollar savings with zero behavior change. Enforce mode serves the cached response directly: the provider is never called, so that request's cost becomes realized savings instead of spend.

• Policy-scoped namespace: tenant, app, model, environment, and custom key-scope dimensions
• Observe mode: see hit rate and would-be savings with zero behavior change
• Enforce mode: serve the cached response, skip the provider call entirely
• Miss-reason tracking, so you know why a request wasn't a hit, not just that it wasn't
• Blast-radius preview before you save a policy: affected apps, eligible request volume, and projected monthly savings

Start with one app, then expand

Turn on observe mode for one high-volume, repeat-heavy app — a support macro or a classification endpoint is a good first target — review a week of hit-rate and savings data, then use the policy blast-radius preview to see projected impact before switching that scope to enforce.

Built for private production AI

Cache lookups sit on the hot path but add no latency budget beyond the lookup itself — a miss falls straight through to the provider. The Visual Policy Builder's save-time preview estimates affected apps, eligible volume, and projected savings from real observed hit-or-would-hit signal, never a fabricated number, and flags when the estimate is scoped to app-level rather than route-level traffic.