Fixes, with a human in charge
A person approves every fix.
It can suggest a prompt change and show replay results for a person to review. Autonomy is earned in steps: observe, recommend, then apply with your approval.
In the product
Fixes, with a human in charge
Suggested fixes waiting for review, shown with demo data.
Fixes drafted from the failures it found
Replayed against your real history before review
Nothing ships until a person merges it
How it works
What happens underneath.
01
Your prompt as the edit surface
When your traces include the system prompt, it reduces that prompt to a template, with slots for the values that change on each request. That template is where fixes are drafted.
02
Checked before you see it
Each drafted fix is replayed against your real history to check it helps without breaking anything, then opened for your review.
03
Autonomy you grant
Start by observing. Move to recommendations when you trust them. Review a suggested change and decide whether to use it.
Tensile Reliability
One product, one loop.
The scorecard, triage, procedure checks and fixes all read the same production traces. Start with one agent.
We build AI agents and keep AI agents reliable, whoever built them.
Tensile AI, formerly TrustEvals
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