We think SMB manufacturers deserve the same intelligence as the Fortune 500.
The tools that let large manufacturers predict failures, optimise resources, and connect maintenance to revenue have existed for decades. They cost $100,000+ per year and require 12-month implementation projects.
We're changing that.
The mission
A 60-person injection molding factory in any city generates thousands of operational data points every day. Its CMMS logs every fault. Its ERP records every order. Its machines emit temperature and vibration data that nobody reads.
Meanwhile, a consultant charges $50,000 to analyse three months of that data and produce a report that's already outdated by the time it lands.
Flarehex is designed to turn that same data into practical operational decisions quickly, run continuously, and improve over time. We believe the insight gap between large and small manufacturers is a solvable problem - and that closing it creates better, more resilient businesses.
Three founding insights
Process mining is underutilised at SMB
The academic research on process mining (PM4Py, conformance checking, variant analysis) is mature and powerful. Almost none of it has been productised for factories with under 500 employees. The tooling exists. The packaging doesn't. We built the packaging.
Maintenance and production should never be separate
Every major enterprise tool treats these as separate domains. IBM Maximo knows about machines. Celonis knows about processes. Nobody connects them at a price SMBs can afford. The causality chain from sensor -> failure -> order -> customer -> revenue is the insight that changes decisions. We built that chain.
IoT value comes from intelligence, not sensors
The industry sells sensors. The value isn't in the sensor - it's in what you do with the data. NVIDIA Jetson edge inference + AWS IoT Core + PM4Py pattern analysis is a stack that makes sensor data actionable without an army of data scientists. We assembled that stack into a product.