Contact Sales
Complete our contact form.
Tignis Overview
Tignis AI process control and analytics-based monitoring software combines the precise insights of physics with the most advance AI and ML data science to give unprecedented automation and process control.
Semiconductor Fabrication
Tignis PAICe Monitor AI-driven anomaly detection and predictive maintenance platform enables process engineers to transforms in-product fault diagnoses into continuous real-time monitoring.
Semiconductor Equipment Manufacturing
Tignis PAICe Maker physics-driven AI computational modeling platform accelerates leading-edge semiconductor manufacturing.
Pharmaceutical and Biotechnology Manufacturing
Tignis physics-based analytics provides proactive optimization with machine learning and digital twin technology.
Case Study: Chiller Plant Monitoring
Optimum Energy uses Tignis software to detect faults in vast amounts of chiller plant sensor data.
WHITE PAPERS
Risk and Faults We Can Detect Using ML and Physics
Maintenance and reliability professionals can preemptively adjust, repair, or replace affected equipment before costly or devastating consequences occur.
OK, I’ve Got 24/7 Monitoring Data. Now What?
By overlaying schematics about systems and their IoT sensors with known facts about the physics of how each element should behave, you can discover design faults, detect potentially miscalibrated sensors, and take corrective action.
How the Special Snowflake Problem Impacts Asset Management – and What You Can DO
24/7 system monitoring data received from parallel but unlike facilities can be optimized and distilled into action.
Bridging the Gap from Data to Value: 3 Ways Physics-based Modeling and Digital Twin Can Help Overcome Sensor Limitation
Facilities are achieving a more durable, digital foundation for understanding and mapping processes and priorities.
GET STARTED TODAY
Tignis can quickly help you improve reliability and efficiency. Getting up and running requires very limited effort on your part and maximizes the assets you already have.
