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Predii's Unnatural Language Processing™ technology assimilates proprietary information about machinery and industrial products to become expert in new domains rapidly. We've been able to use our advanced machine learning systems to map new domains in a matter of days, not months or years. 

We’re committed to eradicating unplanned repairs for OEM products in the industrial world. With the help of predictive analytics, Predii’s software can highlight the parts and equipment that are liable to require replacements, updates and maintenance using macro trends across a broad range of data points, both observed in the specific product and generic to the product type. Technicians can then address these issues before they become problems, preventing costly downtime.

We're working with leaders in the industrial equipment world to identify trends in their data, allowing them to rapidly deploy fixes and repairs in order to save on their service costs. With some of our customers reporting an ROI of 20 times the initial investment, this kind of repair and maintenance technology is truly revolutionizing the business of field repair and maintenance for industrial equipment.



Keep machinery operating at optimal performance by maintaining and servicing with best-practices.

Input: Your product service records, repair manuals, and other service related data. 

Output: Predictive analytics recommendations for preemptive equipment maintenance. Guided repair for service technicians. Recommendations for efficiency based on telemetry data. Alerts for anomalies and outlier behavior.




Track your components success through the warranty and service contract cycles, identifying issues as they happen with related sub-systems in the equipment where they are utilized.

Input: Part codes, warranty claims data, service data, technical information manuals.

Output: Intelligent anomaly detection for your components, and the ecosystem of products they are used in. Guided repair and preemptive maintenance suggestions. 




Predii offers the ability to connect multiple inputs together seamlessly and efficiently. With many sensors in large industrial equipment, outputting a constant feed of data, we eficiently baseline expected behavior and detect anomalies as standard. But the next steps are just as important. Zoning in on the cause, predicting the most likely fix, and guiding the repair process until things are resolved. 




Reduce the time, labor, and costs associated with warranty claims. The software automatically analyzes claims, to pass routine and valid claims while spotting and flagging anomalies.

Input: Claim records and known repair data in the insured domain. 

Output: Automated claim approval process for routine cases. Anomaly flagging, recommended investigation and action for suspect cases. Guided repair system for technicians. 




Guide your technicians with all the pertinent information required to repair your equipment, including parts, labor operations, and most-likely issues. 

Input: All your service and repair data, in any format.

Output: Prioritized recommendations for likely fixes given any set of symptoms. Suggested parts to take on service calls. List of steps to take for recommended fixes, and tests to validate success. 

Ben Johnson

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Ben Johnson
Director of Products, Snap-on