Flutch is an observability and quality control tool for AI pipelines. It helps teams trace every step of a workflow, monitor key metrics, and spot regressions before changes reach production.
Step-by-step quality control
Engineers can run test scenarios, compare prompt and model versions, and track acceptance test pass rates. In one place, Flutch shows quality scores, latency, and per-request cost, making it easier to A/B compare changes and find degradations in chat flows, text generation, and other AI tasks.
Cost and performance monitoring
Flutch collects real-time data on latency, call volume, and spend. Teams can identify the most expensive parts of an AI workflow and optimize model configuration or request routing. It supports working across different frameworks and tech stacks.
Safer releases for AI features
Developers set up tracing, tests, and checks, then roll out changes with a single command. Version history and test cases help reproduce issues and document behavior changes, reducing the risk of unexpected regressions and making AI releases more predictable.
