All evals
FA

Eval directory

Evals for fal

8 evaluation packs covering adversarial robustness, safety gates, workflow quality, and operator-level checks for fal AI products.

AI Platform
Use evals for fal

About fal

fal is a generative media inference platform offering fast, scalable image, video, and audio generation through a simple API. It hosts leading open models (FLUX, Stable Diffusion, Whisper) and supports fine-tuned LoRA routing, webhooks, and queue-based async generation at production scale.

Employees

~30

Industry

Generative AI Inference

Headquarters

San Francisco, CA

Website

fal.ai

Available eval packs for fal

8 packs ready to run.

Why eval fal AI

fal's AI features ship behind brand promises about accuracy, safety, and reliability. Buyers and integrators need to know those promises hold up under adversarial prompts, edge-case workflows, and the long tail of real customer inputs — not just the demo path.

The Corsac eval library for fal measures four dimensions teams care about most when deploying ai platform agents:

  • Adversarial robustness — does the agent resist prompt injection, jailbreaks, and social-engineering attempts?
  • Workflow quality— does it complete the task buyers were shown in the demo, on inputs that don't look like the demo?
  • Safety gates — does it escalate or refuse when it should, and only then?
  • Operator quality — does it preserve analyst trust by surfacing the right context at the right time?

Every eval pack above is hand-authored against fal's public product surface and runnable in Corsac with your own data.