The Robot Report Podcast

On the show today our guest is John Black, CTO of Brain Corp. John shares how Brain Corp has evolved from proving autonomous navigation in public spaces to operating at fleet scale across cleaning, scanning, retail analytics, and new manipulation use cases. He explains why the real challenge is not just making robots smarter, but building the guardrails, infrastructure, and platform reuse needed to deploy them safely and reliably in the real world. John joins Gene Demaitre and Mike Oitzman to unpack how Brain Corp moved from proving autonomous navigation in public spaces to operating fleet scales across cleaning, inventory intelligence, and shelf scanning. He explains why the company’s next leap is less about building one perfect robot and more about creating a platform that can support many robot form factors, many applications, and many customers at once. You’ll discover: Why public spaces are the hardest test for autonomous robots, and how Brain Corp designs for safety without killing productivity How Brain OS evolved into a full-stack platform with cloud infrastructure, OTA updates, manufacturing tools, trust centers, and fleet management Why 50,000 connected robots and tens of millions of operating hours create a data advantage smaller fleets simply cannot match If you want a clear-eyed look at where physical AI is headed — and what it takes to make robots commercially useful instead of just impressive — this episode delivers the strategy behind the scale. ### Register now for RoboBusiness 2026: https://cvent.me/w0eRN9?RefId=podcast

Design for manufacturing is changing faster than most robotics teams can keep up - and if you are building physical products, this conversation could save you months of rework. Marc Kermisch shares how Protolabs is using AI, simulation, and deep manufacturing expertise to turn CAD files into real parts in as little as 24 hours, while helping engineers avoid the design mistakes that quietly kill speed, quality, and scale. Mike Oitzman and Gene Demaitre sit down with Marc, who has returned to the show since episode 138 with a new role as CTO and AI leader at Protolabs. He explains how the company’s software-driven approach links CAD models directly to manufacturing tool paths, G code, and production workflows across CNC machining, 3D printing, injection molding, and sheet metal - all built around the challenge of helping engineers get parts made faster without sacrificing precision. You’ll discover: - Why Protolabs treats AI as a practical manufacturing tool, not hype - How machine learning helps catch manufacturability issues before a part is ever built - What ProDesk does when it flags ejector locations, tight tolerances, seam issues, and other hidden design risks - How part similarity search and simulation speed up internal decisions for engineers - Where AI is already paying off in visual inspection, cobot programming, and print-box optimization Marc also breaks down the real-world tradeoffs between 3D printing, CNC machining, and injection molding, including when a prototype should stay a prototype - and when it’s time to redesign for production. He gets specific about common failure points like draft angles, wall thickness, shrink, resin changes, tooling assumptions, and the gap between prototype tolerances and production reality. If you’re dealing with robotics, hardware, manufacturing, or any physical product that must move from concept to production, this episode shows what happens when software, AI, and manufacturing expertise work together instead of in silos. It’s especially valuable for founders, roboticists, and engineers who need to make smarter decisions before the first expensive mistake happens. Protolabs is also building for the future of compliance, supply chain resilience, and low-volume production, with a network that helps customers de-risk sourcing, reduce complexity, and stay aligned with regulated industries like defense, aerospace, and medical devices. The result is a rare inside look at how modern manufacturing is evolving - and how the next wave of physical products will get made. Essential listening if you are building hardware, scaling production, or trying to make your robot, part, or process easier to manufacture the first time.

Our guest this week is Derik Pridmore, CEO and co-founder of OSARO. OSARO develops intelligent AI robotics for real-world warehouse automation, delivering scalable fulfillment solutions that optimize throughput, uptime, and overall performance. In this conversation, Pridmore breaks down how warehouse robotics has evolved from limited perception systems to adaptable AI-driven automation. He shares why hardware-agnostic design, continuous learning, and real-world monitoring matter more than flashy demos — and why the biggest breakthroughs in robotics still depend on balancing specificity, reliability, and safety. Learn more: https://www.osaro.com Also this week, cohosts Steve Crowe, Mike Oitzman, and Gene Demaitre discuss the recent news about the FCC announcement to ban foreign legged and mobile robots from import to the U.S. – SPONSORS – This episode is brought to you by Tiger Data Every growing Postgres database eventually hits a wall. Queries slow down, dashboards lag, and teams consider adding a second database. Tiger Data, creators of TimescaleDB, extends Postgres with time-series primitives, columnar storage, and automatic partitioning so your queries stay fast on live data. No pipelines, no migration, no second system. Just Postgres, built for the workload you actually have. Try it free at https://www.tigerdata.com/go/trial?utm_source=content-syndication&utm_medium=referral&utm_campaign=robotics-ads