Engineering
Where did it fail?
The span, retry, provider, tool, and error path.
SolutionsRefario / 2026
Different questions. The same production truth.
Engineering, product, finance, and operations should not need separate explanations of the same AI system. Refario gives every team the evidence it needs without breaking the runtime context.
run_6f93One event5.10s · €0.034
01Engineering
02Product
03Finance
04Operations
01 / By responsibility
One operating record, read four ways.
Each team can start with its own question and arrive at the same underlying run, workflow, cost, and policy evidence.
Engineering
- Find failed spans and retries
- Watch latency after releases
- Explain regressions with evidence
Product
- See real workflow outcomes
- Compare behavior by release
- Prioritize high-impact fixes
Finance
- Attribute spend by workflow
- Forecast AI cost
- Give budgets clear ownership
Operations
- Review guardrail coverage
- Monitor tool reliability
- Coordinate incident response
02 / The handoff
Stop handing screenshots between teams.
A cost spike is also an engineering signal. A failed tool is also a product outcome. Refario keeps those relationships visible.
Product
What changed for users?
Workflow success, latency, and outcome trends by release.
Finance
Why did spend move?
Cost attributed to the workflow behavior that created it.
Operations
Was the system controlled?
Guardrail decisions attached to the affected requests.
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Know what your AI system is doing.
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