Rockfish Data, Inc.

Rockfish Data delivers AI-ready data for the connected factory. Manufacturing, supply-chain, and engineering teams increasingly run AI and machine-learning models for predictive maintenance, digital-twin enablement, demand forecasting, quality, and anomaly detection — but those models are only as good as the data behind them, and real operational data rarely contains enough rare events or edge conditions to prove a model will hold up. Founded on Carnegie Mellon University research, Rockfish generates high-coverage, labeled synthetic data from a schema or a sample — preserving the time-series, event-sequence, and session patterns of real operations while injecting the anomalies, drifts, and rare scenarios models must withstand. Teams use Rockfish to test AI workflows and run what-if simulations, evaluate AI and data agents for reliability before production, and share sensor and operations data safely across divisions, corporate partners, and research collaborators. Applicable across automotive, industrial machinery, and aerospace, Rockfish works with companies including Ford.