Evaluation for teams building on fal.ai

fal.ai handles inference — fast queues, model endpoints, and storage for generated clips. Frametail sits on the other side of that call: spans with latency and errors, datasets you pin once, and benchmarks that stay immutable week over week.

If you are shipping a generative video feature on fal, you already feel the gap: playground clips do not become release artifacts, and “it looks better” does not survive a stakeholder review. Frametail closes that loop without replacing fal.

The SDK wraps `@fal-ai/client` so each `run` or `subscribe` call exports spans with inputs, outputs, latency, and errors. Spans land beside video artifacts in the trace viewer — not as a wall of syslog detached from the clip.

From there you can sample production traffic with live scoring rules, or run a full benchmark when you are ready to sign off.

Wire tracing in development, agree on a scorer roster with your PM, pin a dataset of representative prompts, and run a benchmark before you change model endpoints in production. When regressions show up, the trace explains which span failed — not just that “quality dropped.”