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Insights from your assembly line.

Insights from your assembly line.

Small, unexpected defects result in delayed product launches, lost revenues, and brand damage for even the most admired hardware companies. Current quality inspection and failure analysis techniques are labor-intensive and bombard engineers with data that isn’t concise enough to be used efficiently. Iteration is inhibited, even when engineers think they’re working quickly.

Instrumental’s equipment captures images of every unit built at multiple points along your assembly line, and our machine learning-driven tools autonomously learn to identify defects. Instrumental provides insightful, actionable data to help engineers iterate rapidly and prevent small issues from turning into big business problems.

Our founders spent years in factories developing the iPod and Apple Watch, and intimately know the struggles of building high quality products. They are assembling a diverse team who sees inefficiencies as opportunities to develop a system that improves millions of things each day.
Founder and CEO @dfxmachina • System Product Design Lead for Apple Watch • Mechanical Engineering @Stanford University
Total raised

$7.5M

Funded over

1 round

Latest round

Series A (Mar 2017)

Technical Program Manager (技术项目经理)

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Enterprise Account Executive

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Head of Sales

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Machine Learning Engineer

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Full Stack Engineer - Machine Learning Infrastructure

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