Owlpane / Solutions / LLM and AI features
Use cases · built on OpenTelemetryWhat your AI features cost and how fast they answer — without storing prompts.
Calls, tokens, latency and cost from OpenTelemetry gen_ai spans, plus how coding agents are used across your team. Prompt and completion text are not read or shown or shown.
The problem
Why this is hard today
Surprise model bills
Token spend is only visible on the provider invoice, a month late.
Slow answers, no trace
A slow AI feature cannot be split into model time and your own code.
Privacy worries
Logging prompts to debug them puts customer text in yet another system.
What you use
Built from features that ship today
LLM usage
Calls, tokens, latency and cost from gen_ai spans. Prompt and completion text are not read or shown.
AI & MCP →Coding activity
Coding-agent sessions, tool use and reported spend from coding_agent.* and gen_ai.* spans.
AI & MCP →
Requests and spans
The model call sits inside the request waterfall, next to your database and outgoing calls.
APM & tracing →MCP (read-only)
Topology, flows and incidents exposed to your own agents — read-only by design.
AI & MCP →How it works
Three steps
Instrument
Use an OpenTelemetry GenAI instrumentation for your model client.
Send
gen_ai spans go to the same ingest key as the rest of your telemetry.
Watch
See spend and latency per model and per service; alert on either.
Questions
Do you store prompts?
Where Owlpane is narrower
- A value stays blank when the model client or agent did not send it.
More use cases
Related solutions
Send a copy of your telemetry. Change nothing else.
Standard OpenTelemetry in, so you can try Owlpane beside what you run today.
Every new workspace starts with a 14-day Team trial: 50 GB of ingest a month and 30-day retention. No card to start. Documentation · Pricing · Pricing questions