Rethinking Defect Detection in Modern Manufacturing with Matt Puchalski

Robots Don’t Replace Work. They Redesign It. — with Michelle Lo

As robotics and AI reshape manufacturing, the hardest challenge is often not the technology itself. It is helping people, processes, and entire organizations successfully adapt to it. GrayMatter Robotics is tackling that challenge head-on by building AI-powered automation systems designed for real-world manufacturing environments where variability, human expertise, and operational complexity are everywhere. Michelle Lo, Director of Customer Strategy and Success at GrayMatter Robotics, joins Greg to discuss what it actually takes to deploy automation in high-mix manufacturing environments. Drawing from her background in electric vehicles and industrial automation, Michelle shares why successful robotics adoption depends just as much on customer alignment, operator trust, and long-term partnership as it does on the robots themselves. Greg and Michelle explore the realities of manufacturing transformation, from backlog-driven demand and workforce shortages to the nuanced collaboration between humans and robots on the factory floor. They also unpack why configurable automation platforms are enabling faster deployment cycles, how manufacturers evaluate ROI beyond labor replacement, and why “perfect” automation is not always what customers actually want. Highlights: * Michelle’s journey from EVs and automotive manufacturing into customer strategy and robotics at GrayMatter Robotics * Why automation adoption is a long-term transformation journey rather than a one-time deployment * The hidden labor shortages driving demand for automation across industries like aerospace, specialty vehicles, and industrial manufacturing * How GrayMatter Robotics partners directly with operators during deployment to improve adoption and long-term success * The difference between configurable automation platforms and fully custom systems and why deployment speed matters * Why manufacturers evaluate robotics based on throughput, consistency, quality, and capacity rather than simple labor replacement * Lessons from real-world production environments where no two parts, surfaces, or workflows are ever exactly the same * How AI-powered automation systems adapt to high-mix manufacturing environments with constantly changing variables * Michelle’s perspective on humanoid robots and why purpose-built industrial systems are often better suited for manufacturing tasks * The surprising reality that some customers intentionally want “imperfect” robotic finishes to preserve the familiar look and feel of legacy products * How AI and predictive factory intelligence could optimize everything from workflow orchestration to production efficiency in the near future * What makes a successful automation partnership before, during, and after deployment If you are building automation for manufacturing, deploying robotics at scale, or navigating the human side of industrial transformation, this episode offers a grounded look at how AI-powered systems are changing the factory floor while keeping people at the center of the process. Learn more about GrayMatter Robotics: * https://graymatter-robotics.com/ [https://graymatter-robotics.com/] * https://www.linkedin.com/company/graymatter-robotics/ [https://www.linkedin.com/company/graymatter-robotics/] * https://x.com/GrayMatterRobot [https://x.com/GrayMatterRobot] Connect with Michelle on LinkedIn: https://www.linkedin.com/in/michlo/ [https://www.linkedin.com/in/michlo/] Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregtoroosian/ [https://www.linkedin.com/in/gregtoroosian/]

Conviction Before Consensus - Outlander VC with Paige Craig

From bootstrapping a defense intelligence startup with five credit cards to backing some of the most ambitious robotics and autonomy companies in the world, Paige Craig has built his career around one core belief: exceptional people matter more than polished ideas. In this conversation, Paige Craig, founder and managing partner of Outlander VC, joins Greg to unpack how his unconventional path through the Marine Corps, intelligence work, and entrepreneurship shaped his philosophy as an investor. Paige shares why he spends more time analyzing founders than products, how his team evaluates leadership under chaos, and why physical AI and robotics will define the next two decades of innovation. The discussion also dives deep into the realities of robotics deployment, the hidden complexity behind autonomy, and what separates founders who can survive the brutal transition from prototype to real-world scale. Highlights: * Paige’s journey from a difficult childhood and military service to building and bootstrapping a multi-hundred-million-dollar intelligence company * Why Outlander VC invests at the “pre-conception” stage, backing founders before products or customers exist * The 38-point founder framework Outlander uses to evaluate vision, intelligence, character, and execution * Why great founders often emerge from hardship, high agency, and an obsession with solving problems * The loneliness of leadership and why Paige believes the best investors act as true problem-solving partners * How Outlander structures conviction-driven investing, including single-partner authority to write early checks * Why physical AI, robotics, and automation are entering a massive growth cycle driven by AI, manufacturing reshoring, and falling hardware costs * The biggest differences between investing in robotics versus pure software startups * Why cheap, rapidly deployable robots often outperform “exquisite” high-cost systems in the race toward autonomy * Lessons from backing Coco Robotics and Havoc AI, including the realities of deploying robots into unpredictable real-world environments * The overlooked operational challenges of robotics businesses: supply chains, government relations, field operations, and human oversight * Why many robotics founders underestimate the difficulty of scaling hardware systems outside the lab * Paige’s perspective on defense tech investing, the influx of “tourist VCs,” and what founders should look for in strategic investors * The leadership gaps technical founders often face as companies scale, and how mentorship can help engineering leaders grow into organizational leadership roles * Why AI may fundamentally reshape the future role of engineering leadership and startup team structures Connect with Paige Craig on LinkedIn: https://www.linkedin.com/in/paigecraig/ [https://www.linkedin.com/in/paigecraig/] Learn more about Outlander VC: https://outlander.vc/ [https://outlander.vc/] Connect with Greg Toroosian on LinkedIn: https://www.linkedin.com/in/gregtoroosian/ [https://www.linkedin.com/in/gregtoroosian/]

Building Robots People Trust: The Andromeda Vision with Grace Brown

From engineering-first robots to emotionally intelligent companions, Andromeda Robotics is redefining what human-robot interaction can look like in the real world. Grace Brown, founder and CEO of Andromeda Robotics, joins Greg to share her journey from a STEM-obsessed student in Australia to building one of the most distinctive companies in the humanoid robotics space. What started as a response to isolation during COVID has evolved into Abby, a social companion robot designed to bring meaningful connection into aged care environments. Rather than optimizing for flashy demos or industrial efficiency, Grace and her team are focused on something far more complex: building robots that people trust, relate to, and genuinely care about. In this conversation, she unpacks why emotional intelligence is the missing layer in robotics, how design and psychology shape adoption, and what it will take for humanoids to scale in human environments. Highlights: * Grace’s early path into engineering and how a clear passion for math, physics, and problem-solving led her toward robotics from a young age * The founding story of Andromeda Robotics and how strict COVID lockdowns in Australia exposed the real-world impact of loneliness * Why Abby was designed as a character, not a tool, and how Pixar-inspired design principles drive trust and adoption * The overlooked challenge of social acceptance in robotics and why capability alone is not enough to succeed in human environments * Real-world deployments of Abby in aged care facilities and what the team has learned from observing how people actually interact with robots * The importance of personalization in human-robot interaction, from voice tuning to behavioral adaptation for individual users * Why emotional intelligence and “social awareness” will be critical for all robots working alongside humans, even outside consumer settings * The interdisciplinary nature of building social robots, combining engineering, animation, healthcare insight, and operations * How Grace thinks about hiring, from early generalists to later specialists, and why mission alignment is the most important filter * The concept of “anti-selling” during hiring to attract people who truly want ownership and responsibility in a startup environment * Using AI agents internally to accelerate iteration speed and rethink how teams build and operate in modern startups * The broader responsibility of shaping the future of robotics and why who builds this technology will determine its impact on society Learn more about Andromeda Robotics: * Youtube: https://www.youtube.com/@AndromedaRobotics [https://www.youtube.com/@AndromedaRobotics] * Website: https://andromedarobotics.ai/ [https://andromedarobotics.ai/] * LinkedIn: https://www.linkedin.com/company/andromedarobotics/posts/?feedView=all [https://www.linkedin.com/company/andromedarobotics/posts/?feedView=all] Connect with Grace Brown: * Instagram: https://www.instagram.com/grace.jbrown/ [https://www.instagram.com/grace.jbrown/] * LinkedIn: https://www.linkedin.com/in/grace-brown-619b59161/ [https://www.linkedin.com/in/grace-brown-619b59161/] Connect with Greg Toroosian: https://www.linkedin.com/in/gregtoroosian/ [https://www.linkedin.com/in/gregtoroosian/]

Rethinking Defect Detection in Modern Manufacturing with Matt Puchalski

From autonomous vehicles to factory floors, a new wave of vision technology is transforming how manufacturers think about quality. Bucket Robotics is at the center of that shift, bringing simulation-driven inspection systems to an industry long reliant on manual checks and outdated tooling. Matt Puchalski, founder and CEO of Bucket Robotics, joins Greg to share how his experience in self-driving cars shaped a fundamentally different approach to quality inspection. Instead of relying on expensive hardware or months of data collection, his team is using CAD-based simulation to generate training data instantly, unlocking faster deployment, lower costs, and more scalable automation. We explore why quality inspection remains one of the most painful bottlenecks in manufacturing, how legacy vision systems have failed to keep up, and what it takes to build robots that actually work outside of polished demos. Highlights: * Matt’s journey from Georgia Tech and Michelin to autonomy startups and ultimately founding Bucket Robotics * Why quality inspection is still one of the most manual, inconsistent, and frustrating parts of manufacturing * The core insight behind Bucket: applying self-driving car vision systems to factory environments * How CAD-based simulation replaces months of data collection with minutes of synthetic training data * The “sim-to-real” challenge and why perception in changing lighting and environments is harder than it looks * Why most vision systems fail in production and how Bucket is designed for real-world robustness from day one * Lessons from early market assumptions, including why medical device manufacturing was not the right starting point * The economics of inspection: balancing cost, speed, and accuracy across high-mix and high-volume environments * What makes a strong customer fit, from ambiguous defect definitions to expensive rework caught too late * Common objections from manufacturers burned by legacy vision systems and how simulation changes the equation * Why labor shortages and supply chain reshoring are accelerating demand for automated quality solutions * Hiring for empathy in robotics and why understanding the end operator matters more than credentials * The importance of engineers who ship, not just prototype, and why early adopters beat bleeding edge thinkers * Hard-earned hiring lessons, especially the need for teams willing to travel and work onsite with customers * Where robotics is overhyped today, especially around deployment at scale versus polished demos * Why lightweight, lower-cost robotic systems are unlocking a new wave of practical automation * Matt’s view on the future of manufacturing: a hybrid human and robotic workforce rather than full autonomy * Founder reality: why building a company can feel easier than operating autonomous vehicles, but far more isolating * The long-term vision for Bucket Robotics as the “cloud computing moment” for manufacturing quality systems Matt's LinkedIn: https://www.linkedin.com/in/matt-puchalski/ [https://www.linkedin.com/in/matt-puchalski/] Bucket's LinkedIn: https://www.linkedin.com/company/bucketrobotics/ [https://www.linkedin.com/company/bucketrobotics/] Matt's email: matt@bucketrobotics.com [matt@bucketrobotics.com] Bucket's Youtube: https://www.youtube.com/@Bucket_Robotics [https://www.youtube.com/@Bucket_Robotics] Connect with Greg Toroosian: https://www.linkedin.com/in/gregtoroosian/ [https://www.linkedin.com/in/gregtoroosian/]

Building Factory SuperIntelligence with Ariyan Kabir

From disaster response inspiration to reimagining the backbone of global manufacturing, GrayMatter Robotics is tackling one of the largest untapped opportunities in automation: bringing true autonomy to the 90% of factory work still done by hand. Ariyan Kabir, co-founder and CEO of GrayMatter Robotics, joins Greg to share how a firsthand experience with an earthquake in Bangladesh sparked his mission to build intelligent machines that can take on dangerous, tedious work. What started as a question about why robots were not helping in high-risk environments has evolved into a company building “factory superintelligence,” a full stack physical AI platform designed to transform how goods are made. In this conversation, Ariyan breaks down why traditional robotics has struggled in high variability environments, how GrayMatter is bridging the gap with multimodal sensing and foundation models for manufacturing, and why solving these challenges is critical not just for productivity, but for economic resilience and national security. Highlights: * Ariyan’s journey from aspiring astronaut to robotics founder, and how a real world disaster shaped his mission to build intelligent, helpful machines * The hidden reality of manufacturing, with nearly 90% of production still manual despite decades of automation * The core problem GrayMatter is solving, enabling robots to adapt to high variability in materials, environments, and processes * Why physical AI requires more than vision alone, and how multimodal sensing unlocks real world autonomy * Starting with sanding as a strategic wedge, then expanding into grinding, painting, blasting, and inspection through transferable learning * The power of data, building one of the largest manufacturing datasets to train foundation models for materials and processes * Robot scientists and domain specific AI agents that compress process optimization timelines from months to days * How optimizing human, robot, and AI workflows can drive massive gains, including tripling throughput without adding robots * Lessons from early deployment challenges, from consumables to real world variability, and how they shaped more intelligent systems * The importance of an adoption playbook, and why deploying robotics successfully depends on process and people as much as technology * Ariyan’s perspective on talent, why high agency and system level thinkers are the most valuable builders in the age of AI * What is still missing in robotics today, and why domain specific intelligence layers are the next frontier * A vision for the future, rapidly reconfigurable, fully autonomous factories that can adapt in real time to new products and global needs For founders, engineers, and operators thinking about the future of manufacturing, this episode offers a deep dive into how physical AI will reshape the industrial world and why the race to build intelligent factories is just getting started. Learn more about GrayMatter Robotics: * https://graymatter-robotics.com/ [https://graymatter-robotics.com/] * https://www.linkedin.com/company/graymatter-robotics/posts/?feedView=all [https://www.linkedin.com/company/graymatter-robotics/posts/?feedView=all] * https://x.com/GrayMatterRobot [https://x.com/GrayMatterRobot] Connect with Ariyan Kabir: * https://x.com/ariyankabir [https://x.com/ariyankabir] * https://www.linkedin.com/in/ariyankabir/ [https://www.linkedin.com/in/ariyankabir/] Connect with Greg Toroosian: https://www.linkedin.com/in/gregtoroosian/ [https://www.linkedin.com/in/gregtoroosian/]