3 posts tagged with "finops"

Traditional caching keys on an exact match: same input, same cached output. That works for HTTP and falls apart for language, because two prompts can be worded completely differently and mean exactly the same thing. "What's your refund policy?" and "How do I get my money back?" would miss an exact-match cache every time — and you'd pay to generate the same answer twice.

Semantic caching keys on meaning instead of bytes. But a cache that stores prompts and responses is also a governance surface: it can quietly hold raw PII, and it can quietly keep charging you for calls that never happened. Both are failure modes a governance platform has to close by default — which is why, in DVARA, the semantic cache lives inside the same governed path as Policy-as-Code and PII redaction, not off to the side.

The first LLM invoice that makes someone's stomach drop is a rite of passage. Spend is driven by token counts nobody was watching, spread across teams nobody was attributing, on models nobody chose deliberately. By the time it shows up on a bill, the money is gone and the cause is a forensic exercise.

Most tools answer this with a dashboard — visibility after the fact. That's the difference between observation and governance: a dashboard tells you what you spent; a governed control point can stop you from spending it. Real cost governance moves control upstream, to the moment each call is made — attributing it, and enforcing a budget on it, before the request leaves your perimeter. That enforcement lives in the DVARA LLM Gateway, the data plane of the AI governance platform.

Your API gateway handles TLS termination, rate limiting, and request routing. It does these things well. But when your traffic carries prompts, tokens, tool calls, and model-specific payloads, an API gateway becomes a passthrough — it can see the HTTP envelope but not the AI semantics inside it.