From Downtime to Uptime: How Industrial AI Is Bringing Actionable Intelligence to the Factory Floor

Industrial AI is cutting through manufacturing downtime with a technician-first approach to AI-powered maintenance. Founded by manufacturing engineers Rodrigo Valladares and Jose Dos Santos—formerly of Medtronic and Tesla respectively—the company was born out of real frustrations experienced on the factory floor. Seeing how underserved factories are by traditional software, the duo set out to transform the way industrial teams solve problems by turning underused documentation into instant, trusted troubleshooting steps.

By building an AI layer that integrates seamlessly with existing systems like SAP and Maximo, Industrial AI helps technicians go from “it’s down” to “it’s fixed” faster—without requiring a full tech overhaul.

Business Now caught up with Rodrigo Valladares to explore the philosophy behind Industrial AI, how their engineering backgrounds shaped the product, and what the future holds for AI-powered factory operations.

What inspired the creation of Industrial AI, and how does your background in manufacturing engineering influence the product’s vision?

We’re obsessed with factories and saw how underserved they are by software. My cofounder and I are manufacturing engineers. He was at Tesla, I was at Medtronic. We kept talking about how AI could make our jobs easier and save real money. So we started meeting on video calls on weekends, built small things, and that turned into Industrial AI. Our focus is practical: shorten the path from “it’s down” to “it’s fixed.”

The biggest influence from our backgrounds is that we’ve been on the floor. We know what sounds great on paper often won’t work in a real plant. We know these guys. We’re not building a dashboard to track metrics. We’re building a tool for technicians that makes their job easier, because if it doesn’t make their job easier, they won’t use it.

Industrial AI leverages factory documentation to reduce downtime. What makes documentation such an untapped asset in manufacturing?

The answer to an equipment failure is usually in a manual, a report, or a resolved work order, but finding it under pressure is not practical and can be a waste of time. The manual might be 30 pages and the one line you need is buried in there.

Also, techs are busy fixing—they don’t have time to write perfect notes of what they did, and they don’t really benefit from doing it since they know they won’t bother looking for it in the future. When they can log what happened with voice as they work, you capture richer detail in the work order record. Then, we make all of that findable by just telling the AI what’s wrong. It’ll show the step-by-step instructions on how to fix it and include the source so people trust it.

How does Industrial AI differ from traditional CMMS or maintenance systems already used in factories today?

We’re not a CMMS. Your CMMS is the system of record. Industrial AI is the system of action on top. We plug into Maximo, SAP, or whatever you use, read your manuals and history, and return step-by-step troubleshooting inside your current workflow. No rip and replace. Just faster, trusted answers with citations.

What were some early challenges in training the AI to understand technical manuals, downtime reports, and troubleshooting notes effectively?

Relevance was tough. With lots of documents, the AI might pull something technically correct but not the most accurate for the situation. We rebuilt retrieval with agents and a knowledge graph that organizes by asset, component, and symptom. If the issue mentions a motor, we prioritize motor content and related work orders, build a tighter candidate set, then rank and cite. That made answers more useful on the floor.

As AI adoption in manufacturing grows, what’s your vision for how tools like Industrial AI will shape the future of factory operations over the next 5 years?

In five years, plants that lean into AI for maintenance will cut downtime and ramp new techs faster. The normal flow will be voice in, clear steps out, with parts, sources, and updates captured as you work. With the skills gap growing and experts retiring, this won’t be optional. In 10 to 15 years, most big factories will run Industrial AI as standard.

For more information, visit: https://www.industrialai.tech/

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