FLIR Systems had run out of room to grow — literally. Their infrared sensor manufacturing and calibration lines were constrained by factory floor space and by the throughput and quality limits of manual labor. We led the project to fully automate their infrared camera assembly and calibration. The r
Results at a glance
Increase in output per square foot
Continuous production
FLIR was hitting a hard ceiling on two fronts at once. On the factory floor, physical space had become the bottleneck: their infrared sensor manufacturing and calibration lines simply couldn't fit more capacity into the square footage available. At the same time, they were constrained by human throughput — the speed, consistency, and quality that manual assembly and calibration could sustain.
Infrared camera calibration is precise, repetitive, and unforgiving work. Scaling it the traditional way would have meant more floor space, more people, and more variability in quality — none of which FLIR could afford as demand grew. They needed to break the link between capacity and headcount, and between output and floor space.
We led the end-to-end effort to fully automate FLIR's infrared camera assembly and calibration product lines. Rather than adding people and space, we re-engineered the lines so the machines do the precision work — consistently, continuously, and in a fraction of the footprint.
Automation didn't just relieve the bottleneck — it redefined what FLIR's existing facility could produce. By taking the precision work off the floor staff and running it continuously, we lifted both the density and the duty cycle of the operation without growing the team.
Services used
Gaize had the science to detect drug impairment in real time but not the working technology — a prior contractor engagement left them without a functioning detection pipeline. We ran an extensive data-science program to extract reliable impairment signals from their high-frequency eye-tracking data,
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Book your assessmentVISIE's engineering team was swamped — their engineering and quality-control processes were almost entirely manual, capping how much the team could ship. We analyzed their ecosystem and requirements and delivered a thorough, mathematically derived and validated proposal and design to streamline both
