How teams ship reliable AI faster with synthetic time-series data.
Real-world results from enterprises using Rockfish to generate privacy-safe, high-coverage data for ML training, evaluation, and scenario modeling.
Finding high-probability renters with synthetic booking data.
Peer-to-peer car-sharing marketplace · Peru
Rento Perú trained a customer-propensity model on Rockfish synthetic booking data — breaking past a two-year data ceiling to rank its customer base and deliver a high-precision outreach list that converted far above the organic baseline.
conversion
engagement
random list
Powering AI data agents with synthetic behavior data.
with NEXA · ACM CAIS 2026
Conviva used Rockfish AgentFuel to build a persona-driven pipeline that joins web behavior to chat — reproducing a real intent-to-conversion signal and four labeled failure modes to stress-test its NEXA analytics agent against ground truth.
reproduced
patterns
pattern set
Enhancing supply chain intelligence with synthetic data.
Tier-1 Automotive OEM
A global Automotive OEM used Rockfish DataFuel to generate a scalable, rule-compliant synthetic order bank — enabling buildability validation and AI-driven analysis across thousands of feature families.
scale-up
configurations
generation
Additional case studies publishing soon.
We're working with customers across telecom, cybersecurity, networking, and financial services to publish their results. Want to see what Rockfish can do for your data?
Want to see what this looks like for your data?
Discover how privacy-preserving synthetic time-series data can accelerate your ML development, enable scenario modeling, and unlock new collaboration opportunities — without the data sharing risk.
Book a Demo →