LLM observability · One interaction record
See what every AI call actually did.
Trace local and hosted LLM calls with the same vocabulary. See the route, model, latency, cost, failure, fallback, prompt version, and quality signal behind each interaction.
Trace the whole route
A 200 response does not tell you whether the system worked.
The answer may have come from the wrong model, crossed to a hosted fallback, taken too long, cost more than expected, or used a stale prompt version. Optimaiz joins those facts to the interaction that produced the answer.
Begin with observability
Keep inference exactly where it is.
Instrument current OpenAI, Anthropic, or Gemini calls. Measure cost, latency, errors, and quality before deciding whether any workload belongs on local capacity.
Then add local capacity
Compare both paths side by side.
Run a bounded workload on an approved computer. The same interaction model shows whether local execution actually improved cost, latency, reliability, and quality.
Retention is not transit
Choose what the trace stores.
Metadata mode
Keep route, model, timing, token, error, fallback, and supplied identifiers. Prompt and response content are excluded from long-term interaction history.
Full-content mode
Retain permitted prompt and response data for debugging, review, evaluation, and prompt improvement. Use only where content capture is allowed.
Managed calls still send request data through Optimaiz in transit. Metadata mode changes long-term trace retention; it does not create a device-only network path.
LLM observability FAQ
The operational questions
What is LLM observability?+
LLM observability links each AI interaction to its route, actual model, prompt or prompt version, latency, tokens, cost, errors, attempts, fallback, and quality signals so teams can explain system behavior.
Can Optimaiz observe an existing hosted LLM without moving it locally?+
Yes. Instrument existing OpenAI, Anthropic, or Gemini calls first. You can add local capacity later without changing the purpose of the trace.
Can I avoid storing prompts and responses?+
Yes. Metadata-only tracing excludes prompt and response content from long-term interaction history while retaining operational measurements and identifiers.
Why does hybrid AI need route-aware traces?+
The requested route and actual route may differ when reassignment or hosted fallback is permitted. Execution location affects cost, privacy boundaries, available models, and recovery behavior.
Observe first. Move traffic with evidence.
Start with existing model calls, then add local compute when the workload earns it.
Start free →