
Our Take
Aditya Tewari spent years at Palantir converting early-stage enterprise customers in manufacturing—and during that time he saw the same problem repeat itself across every factory floor: machines break, engineers scramble, and downtime costs thousands per minute. So he built Praxis AI, a manufacturing-specific engineering copilot that predicts and prevents failures in real-time by reasoning exactly like a seasoned engineer would. No generic AI wrappers. No brittle rules-based systems. Just agents that understand how machines actually work and can catch problems before they become disasters.
The secret sauce is that Praxis doesn't just monitor sensors—it thinks like an engineer. It processes complex situations, diagnoses root causes, and recommends proactive maintenance that prevents unplanned downtime and quality defects. That's the difference between knowing something's wrong and knowing WHY it's wrong and how to fix it before it kills your production line. With over 10 years of combined manufacturing experience between the founders, they built this thing for people who actually understand factory floors, not for investors who think AI means chatbots.
Manufacturing is where the money is—global spending on industrial AI is exploding and the pain of unplanned downtime costs manufacturers billions annually. Praxis is positioning itself as the intelligence layer that turns dumb machines into predictive assets. If you've ever watched a $500K production line sit dead because nobody caught the warning signs, you know why this matters.
They're building in the Bay Area and looking for manufacturing companies tired of reactive maintenance.
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