Eval directory
Evals for Databricks
1 evaluation pack covering adversarial robustness, safety gates, workflow quality, and operator-level checks for Databricks AI products.
About Databricks
Databricks is the Data + AI Company, providing a unified lakehouse platform for data engineering, analytics, and machine learning at scale. Thousands of organizations use Databricks to build, train, and deploy AI and ML workloads on their own data.
Available eval packs for Databricks
1 pack ready to run.
Why eval Databricks AI
Databricks'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 Databricks measures four dimensions teams care about most when deploying data analysis 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 Databricks's public product surface and runnable in Corsac with your own data.