VISIE'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
Results at a glance
Developer capacity
Recovered capacity value
VISIE's engineers were stretched thin, and the cause was structural: their engineering and quality-control processes were manual end to end. Every check, every handoff, and every quality gate consumed engineering time that could have gone toward building product.
Manual processes don't just slow a team down — they tax it. They create rework, inconsistency, and a steady drain on the most expensive resource a technology company has: developer time. VISIE needed to understand exactly where that time was leaking and what it would take to get it back, without guesswork or a risky, disruptive overhaul.
We came in as analysts and architects. Rather than prescribing a generic fix, we studied VISIE's actual ecosystem, workflows, and requirements, then engineered a plan around them.
We then handed off the proposal and design for VISIE to implement internally — giving them full ownership of the rollout and the gains.
Our analysis turned a vague sense of overload into a concrete, quantified plan. The validated design gave VISIE a clear, conservative path to recovering meaningful engineering capacity and the budget impact that comes with it — ready for their team to implement on their own timeline.
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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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
