AiThority Interview with Michael Corr, CEO & Co-Founder, Duro

Michael Corr, CEO & Co-Founder at Duro chats about the benefits of AI driven PLM systems in this catch-up with AiThority.com:

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Please take us through your journey and tell us about Duro. What inspired the platform?

Before founding Duro, I spent years as an electrical engineer in the hardware space. Across the board, I saw the same problem: teams were building advanced electromechanical products but relying on outdated systems to manage product data. Collaboration would break down, design decisions would get lost, and critical sourcing details would be buried in spreadsheets. Duro was born from the belief that hardware teams deserve tools as agile and intelligent as their products. Our mission is to centralize product data, automate tedious tasks, and make lifecycle management truly collaborative.

Duro’s story is one of timing, persistence, and market clarity. We bootstrapped early on, when VCs were focused on fintech and machine learning, not hardware. Then COVID hit, and the fragility of global supply chains became impossible to ignore. Manufacturing returned to the spotlight, and investors started paying attention. In 2021, we raised pre-seed funding and a seed round in 2023, backed by investors in LA and New York. As reshoring has gained momentum and the Fourth Industrial Revolution has taken hold, it’s evident there is a massive market need for a modern PLM (product lifecycle management) platform purpose-built for hardware, supply chain, and manufacturing teams.

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Can you briefly highlight some recent feature enhancements that have benefited end users?

We pride ourselves on being known as the “programmer’s PLM” and providing an intuitive interface for both beginner and power users. Our most recent advancements have focused on reducing friction in the product development lifecycle through AI-native features. For example, we’ve introduced natural language validation rules for users to generate logic like “weight under 2 kg” or “must meet RoHS compliance” without writing any code.

We’ve rolled out predictive change analysis and AI-powered sourcing recommendations, giving engineers instant feedback on how design updates will impact suppliers, compliance, or costs. These tools help teams move faster while reducing risk, and no consultants are needed. We’re also excited to offer workflow editor wizards, a powerful YAML editor for configuration management, and expanded our GraphQL API capabilities—all part of our API-first architecture and fully powered by AI.

What do most industry users get wrong when it comes to understanding, deploying, and optimizing product lifecycle tools? What can help here?

Too many teams still treat PLM as a digital filing cabinet. But PLM is far more than document storage; it’s the connective tissue of modern product development. When used correctly, PLM aligns design, sourcing, and manufacturing teams through a single shared source of truth. What holds companies back is often poor usability, legacy software that doesn’t fit agile workflows, or a lack of integration across the stack.

Many don’t realize that legacy tools, vendor lock-in, and reliance on consultants can be easily avoided. PLMs should be flexible and serve as the digital thread that holds everything together. What helps is adopting a PLM combined with PDM that’s cloud- and AI-native, configurable out of the box, and able to grow with your organization.

How can AI play a significant role in PLM software?

AI supercharges what PLM was always meant to do: reduce manual work, surface insights, and help teams move faster with fewer errors. AI-driven PLM can generate metadata from CAD files, run predictive impact analysis on design changes, and optimize BOMs based on real-time sourcing conditions. The technology empowers non-technical users to search product data using natural language instead of complex queries.

When AI is built into the core of PLM, not bolted on, it transforms the system into a real-time engine for decision-making and collaboration. It keeps the digital thread intact, ensuring teams have access to accurate, current data across design, sourcing, and manufacturing. The result is AI-powered automation and intelligence in every workflow, helping hardware teams reduce risk, accelerate iteration, and bring better products to market faster.

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When it comes to product data management, what works best to ensure processes and insights remain seamless?

It starts with centralization. A fragmented tech stack breeds errors, duplicate data, and wasted time. The best PLM solutions include PDM and act as the hub of the digital thread, connecting CAD, ERP, MES, and supply chain tools in real time. From there, intelligent automation becomes critical. Engineers can focus on designing instead of managing files or chasing updates when validations, sourcing recommendations, and compliance checks happen automatically.

Research has shown that strong UI/UX leads to higher user productivity, and intuitive UI features empower users to “own their experience.” That’s why the key is making these workflows fast, flexible, and accessible to every team member.

Modern PLM systems need a low-code, programmable interface that allows infinite extensibility and an API-first approach that exposes everything to integration partners. This combination ensures product data stays clean, current, and connected across the full product lifecycle.

What are your thoughts surrounding the future of SaaS and especially PLM software?

PLM software is finally catching up to the expectations of modern engineers. We’re moving from heavy, consultant-led deployments to fast, flexible SaaS platforms that scale with your business. The future is API-first, AI- and cloud-native, and usability-focused. As hardware becomes more complex and supply chains remain unpredictable, companies need tools that help them act quickly and collaboratively.

SaaS PLM platforms that combine intelligence with interoperability will lead the way. And much like the shift we saw during COVID, the current climate of tariff uncertainty and supply chain instability could accelerate SaaS adoption, especially with PLM  as the anchor in the tech stack.

Any thoughts you’d leave us with (tips, insights, AI best practices), to wrap up?

If you’re building hardware or innovative products in 2025, your PLM platform shouldn’t slow you down; it should be one of your competitive advantages. Look for tools that support agile development, plug into your existing stack, ideally include PDM, and can evolve with your product. And don’t wait until something breaks to modernize your systems.

The earlier you centralize your product data and build a digital thread, the easier it becomes to scale, innovate, and deliver great products. You don’t need to get locked into vendors or rely on multiple contractors; you only need the tools your team actually needs. If your engineering team is losing time on innovation or key tasks because of admin overhead, something’s not working, and its time to make a change.

[To share your insights with us, please write to psen@itechseries.com]