What usually happens
•A customer says the model answer changed overnight.
•Someone drops a screenshot, prompt, and logs in Slack.
•The eval failure is discussed in another thread.
•By the time a ticket exists, half the debugging context is gone.
What Strukt does
•Creates or updates tickets from model regression threads.
•Attaches prompts, eval notes, logs, screenshots, and customer details.
•Links GitHub work, PRs, and commits.
•Keeps debug and deployment status visible in Slack.
Why teams use it
•Fewer half-empty model bug tickets.
•Less time rebuilding the customer-specific setup.
•Prompt and eval context stays with the fix.
•AI rollout work is easier to hand off.
Example workflow
•Customer reports a bad model response
•Prompt, logs, and screenshot get attached
•Strukt creates or updates the issue
•Engineering links eval and GitHub work
•The customer-facing team sees the fix move
Setup notes for connecting your tools.
Connect tasks to the code that fixes them.
Strukt links issues to PRs, commits, repositories, and comments so non-engineering teams can follow progress.
USE CASEGive every task the details people need to act.
Strukt keeps customer details, files, code, screenshots, and source threads attached as work moves across teams.
USE CASEMost customer feedback dies in Slack threads.
Strukt turns customer conversations into tracked work automatically.
INTEGRATIONGitHub integration
Attach PRs, commits, and repositories to the task, bug, or request they address.