Rockfish Data develops a synthetic data generation platform designed for teams building and evaluating AI agents and machine learning models. The platform produces domain-specific, high-fidelity, labeled data, with a particular emphasis on generating rare edge cases and unexpected scenarios that are difficult to source from real-world datasets. This allows teams to identify model failures before deploying to production.
The company's core technology addresses data scarcity as a bottleneck in the development of production-ready time-series ML systems. The Rockfish Data Platform can generate realistic scenarios from a schema or existing samples, pairing them with answers to support rigorous AI evaluation workflows. It is built to support secure deployment within customer environments, reflecting an emphasis on privacy and security.
Rockfish Data was built by researchers from Carnegie Mellon University. The company operates at the intersection of synthetic data generation, AI evaluation, and machine learning testing, serving teams in the AI/ML development and data science verticals.
