Atlas Labs launches SignalNet to monitor AI model drift for regulated apps

Tech · 5 min read

Atlas Labs unveiled SignalNet, a monitoring and observability product for production AI systems targeting finance, healthcare, and government customers. SignalNet tracks distribution shifts, calibration drift, and concept drift, and surfaces root-cause indicators with automated rollback recommendations.

SignalNet emphasizes privacy: telemetry runs local aggregation and differential privacy mechanisms before reporting, allowing teams to monitor models in sensitive environments without exposing raw user data. The system also maps model predictions to upstream data slices to isolate problematic cohorts.

The company raised $22 million led by Vertex Growth to build SOC-compliant hosting, add more connectors for enterprise MLOps stacks, and grow an on-call incident response team specialized in AI failure modes. Atlas Labs says SignalNet will be generally available by Q1 2027.