Psistar provides an operational‑logic platform that converts raw sensor data from high‑risk industrial systems into real‑time, physics‑based predictive insights.
Funding
Funding not disclosed
Founders
Product
Problem
High‑stakes industrial and infrastructure systems generate massive streams of sensor data, but operators often face information overload and lack clear guidance on how to prevent failures. This leads to unplanned downtime, costly disruptions, and reliance on a limited pool of expert operators.
Solution
Psistar delivers an “operational logic” platform that transforms raw sensor inputs into real‑time predictive insights. By modeling the underlying physics of pressure, flow, temperature, and related variables, the system forecasts anomalies, identifies causal factors, and generates actionable recommendations for operators. The platform provides the expertise of top operators at every console, 24/7, even when connectivity is intermittent, reducing guesswork and unplanned downtime.
Target Audience
Primary customers are operators and control rooms of large‑scale, high‑risk facilities such as energy plants, manufacturing complexes, and critical infrastructure providers that depend on continuous, reliable operation.
Features
- Physics‑based modeling engine that interprets sensor data as a coherent representation of system behavior
- Real‑time anomaly forecasting with confidence scores to prioritize emerging issues
- Causal analysis that explains the root physical drivers behind predicted failures
- Automated, step‑by‑step operational recommendations delivered directly to control room interfaces
- Offline capability ensuring continuous insight delivery during connectivity loss
- Integration layer that consolidates data from heterogeneous sensor networks without requiring additional dashboards