Evaluate Analytics Agents with Realistic, High-Coverage Synthetic Test Suites
Rockfish generates rich, labeled synthetic scenarios and automated Q/A test cases to rigorously evaluate analytics agents — eliminating blind spots, reducing hallucinations, and improving reliability before deployment.
Why Analytics Agents Fail in Real-World Use
- Agents hallucinate responses
- Incorrect answers confused users
- No realistic or labeled datasets exist
- Current testing has major blind spots
- Minimal scenario diversity → easy tests
- No regression testing across versions
Agents deployed with insufficient testing->incorrect responses->loss of customer trust
The Gaps in Today's Agent Testing
The Rockfish Evaluation Workflow
Rockfish Generates the Patterns Agents Must be Tested Againts
Univariate Patterns
Spikes, anomalies, seasonality, trends, noise.
Multivariate Patterns
Cross-correlation, lagged effects, interaction dynamics.
Operational Patterns
Bursts, cascades, drift, periodic shifts.
Automated Q/A Test Cases With Ground Truth
> NL question
> Expected NL answer
> SQL query
> Yes/No correctness label
> Versioned test suites for regression
Ensure Your Analytics Agents Are Trustworthy Before You Ship
Rockfish delivers realistic, high-coverage test suites to eliminate hallucinations and ensure reliability.