Define custom criteria, track performance metrics, and compare results historically.
Get context-aware suggestions and real-time feedback for your instructions.
Share criteria libraries, best practices, and insights across your team.
Track changes, compare versions, and maintain a history of your instruction improvements.
Measure and validate improvements with comprehensive metrics and analysis.
See how teams are improving their AI systems with eval.dog
eval.dog reduced our prompt engineering cycles by 60% while improving output consistency.
Finally, a systematic way to measure and improve our AI instruction effectiveness.
The collaborative features transformed how our team develops and maintains AI systems.