About

FactR is a Canadian SaaS company focused on enabling intelligent, Agentic AI enabled decision-making across complex data environments. Its flagship product, DataPeak, is a no-code, agentic AI platform that automates the collection, integration, and analysis of operational data. The platform is designed to help organizations streamline workflows and scale business processes with greater precision and efficiency. FactR, established in 2018, serves clients across multiple sectors, including advanced manufacturing.

Project

DataPeak has been commercially launches and is being used to support digital transformation and intelligent data automation. Using existing vibration and wear sensor data collected from robotic equipment, the project will analyze how well this data can be used to anticipate mechanical failures before they occur. The research will compare traditional analysis methods with insights generated by DataPeak, an agentic AI platform that automates the analysis of complex operational data to detect patterns, anomalies, and emerging failure risks. By applying machine learning models to historical sensor data, the project aims to create an automated predictive maintenance plan. This would allow systems to detect early warning signs and recommend maintenance actions before costly breakdowns, improving efficiency, reducing downtime, and advancing equipment health monitoring.

Impact & Outcomes

By the end of this project, FactR will have a fully validated AI model, capable of predicting potential equipment failure based on historical vibration and wear data, an automated maintenance planning workflow, and documentation outlining model design, training methodology, assumptions, limitations, and validation metrics. Once field testing and integration are complete, it is anticipated that 2 new technical roles will be generated at FactR. New revenue streams will be generated through licensing and implementation of DataPeak. The Ontario Manufacturing sector in general could benefit through investment in the technology upon successful demonstration of its effectiveness through this project, resulting in increased availability of equipment, and improved Overall Equipment Effectiveness.