Adapt it to the work
Test changes against real past cases
Save a finished conversation as a test, and check every later draft against it before you trust the new release.
Replay a draft against conversations that went right, without repeating their effects on the systems they touched.
What this changes for your team.
Save as a test turns a finished conversation into one the agent is checked against. Yekar.AI replays its messages against your latest changes and answers each tool call from what the tool returned at the time, so nothing runs for real and no email is sent twice. The report puts what the agent did beside what it did then, and the test's checks decide whether it passed.
How it works in practice.
- 01
Save a representative finished conversation as a test, and add checks on what a good answer does.
- 02
Run it against your latest changes; tools answer from the recording, without calling those systems again.
- 03
Read the result check by check, with the replies, tool calls and token use beside the original's.
What you can plan around.
What to expect, including limits that matter to your team.
A test keeps its own copy of the conversation, so it still replays months later and survives the conversation being deleted.
Recorded tool answers are reused during a replay; a call the conversation never made is reported and is not run.
A replay with no checks reports as unscored rather than passing, so a difference in wording is never mistaken for a regression or a pass.
Bring one real process
See how Yekar.AI fits the way you work.
Start with a job your team already owns, plus the tools and decisions around it.
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