Falkonry’s time-series AI finds abnormal equipment behavior in industrial sensor streams, weeks before failures surface.
Falkonry specializes in operational time-series intelligence. Its platform learns the normal behavior of equipment from continuous sensor and PLC data, detects novel conditions automatically, and helps engineers diagnose what those conditions mean — published work cites detecting precursor conditions 3 to 10 weeks before breakdowns in steelmaking.
A key design choice is no-code operation: plants can be connected within hours and plant engineers, not data scientists, interpret and refine the results. Falkonry has been deployed across semiconductors, metals, oil and gas and defense, including work with U.S. government customers.
Most industrial monitoring is threshold-based: an alarm fires when a sensor crosses a limit, usually when the problem is already advanced. Falkonry’s unsupervised approach learns each asset’s normal multivariate behavior and flags novel patterns earlier, which published cases describe as weeks before functional failure. That lead time changes what maintenance can do: order parts, schedule downtime, and avoid scrapping product. The no-code premise matters because plants cannot hire data scientists for every line; engineers connect data sources and interpret behavioral patterns themselves. Feedback from those engineers tunes the system over time. Deployments in steel, semiconductors and defense suggest the approach generalizes across heavy industry where equipment behavior is complex but data is abundant.
Feedback from plant engineers improves the system continuously, and the no-code setup means a line can be connected in hours rather than after a months-long modeling project. Where equipment failures are expensive and diagnostics complex, weeks of warning translate directly into avoided downtime, saved product and calmer maintenance planning.
Analytics tools in this category succeed when they close the gap between data and decision: models must surface the right signal at the moment of action, integrate with operational systems, and keep accuracy visible as conditions drift over time.
Falkonry is sold through enterprise agreements scoped to plants and use cases.
Heavy industry and defense operations that need earlier warning of equipment problems than threshold alarms provide.
No — access is through enterprise evaluation and deployment agreements.
Falkonry ingests industrial data streams and integrates with operational platforms; integration specifics are handled per customer.
Versus vibration-only monitoring, Falkonry analyzes arbitrary multivariate sensor streams and finds unknown failure modes, though it needs clean historical data to learn normal behavior.