Why did support-resolution become 2.4 seconds slower?
A shipping tool timed out once and retried on 18% of runs.
ProductRefario / 2026
Everything that happened, in order.
Refario turns a production AI request into one readable record—from routing and model calls to tools, policy decisions, cost, and final output.
01Requestreceived18ms
02Agentrouted62ms
03Modelgenerated1.42s
04Toolretried2.84s
05Outputdelivered5.10s
Run cost€0.034+€0.009 retry
Latency5.10sTool path +2.41s
PolicyPassed6 / 6 rules
01 / The operating record
See the system behind every answer.
Raw logs tell you that something happened. Refario shows how the parts of your AI system worked together—and where the result changed.
01
Runs
Every request, model call, tool, retry, and output on one readable timeline.
02
Cost
Spend attached to the workflow and customer behavior that created it.
03
Control
Guardrails and incidents visible beside the execution path they affect.
04
Tools
MCP and internal tool health without breaking the trace into another product.
02 / Investigation
Move from a changed metric to the exact runtime cause.
Follow the signal without changing tools or rebuilding context at every step.
01
Notice
A workflow slows down, cost moves, or failures cluster after a release.
02
Follow
Open the affected run and trace its model, tool, retry, and policy path.
03
Explain
See the dependency, routing decision, or fallback that changed the outcome.
04
Act
Tune the workflow, update a guardrail, or share the evidence with the owner.
03 / Questions answered
Built around decisions, not dashboard inventory.
The value of observability is the confidence to answer an operational question while it still matters.
Which path is increasing cost per customer?
The provider fallback adds €0.009 per affected request.
Did the policy still protect the output?
Yes. Six rules ran and the sensitive-data check passed.
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