Restaurant AI

David Corts: The Intelligence Layer Your Kitchen Has Been Missing

In this episode of the Restaurant AI Podcast, Matt Wampler sits down with David Corts, CEO of Fresh Technology, the company behind Fresh KDS. David spent 25 years in enterprise software watching digital transformations unfold across media, e-commerce, and ad tech before betting everything on the most underleveraged asset in the restaurant industry: the kitchen. Matt and David dig into why billions of dollars have flowed into front-of-house technology while the kitchen has been running on paper tickets and gut instinct. David breaks down why average ticket time is one of the most misleading metrics in the industry, what a true system of intelligence for the kitchen actually looks like, and why the Fresh KDS composable layer gives operators the flexibility they have always wanted without the complexity that comes with it. The conversation goes deep on the dot-com parallel playing out in AI right now, why doing AI for the sake of AI is the fastest way to build nothing, and how Fresh KDS is partnering with ClearCOGS to bring predictive analytics directly to the kitchen screen, turning a reactive operation into a proactive one. Connect with David Corts on LinkedIn: linkedin.com/in/davidcorts Learn more about Fresh KDS: freshkds.com Connect with Matt Wampler on LinkedIn: linkedin.com/in/matthewjwampler Learn more about ClearCOGS: https://www.clearcogs.com [https://www.clearcogs.com]

The Brain of the Restaurant: How AWS Thinks About AI with Deborah Matteliano

In this episode of the Restaurant AI Podcast, host Matt Wampler, Co-Founder and CEO of ClearCOGS, sits down with Deborah Matteliano, Global Head of Restaurants and Food Tech at AWS. A founding member of the Uber Eats sales organization who scaled the platform to over 200,000 restaurants across the US and Canada, Deborah later led Uber's Virtual Restaurants segment to 700% global growth before joining Amazon Web Services, where she now advises the world's largest quick service restaurants, food tech brands, and delivery platforms on AI and cloud strategy.  Matt and Deborah dig into why 90% of the world's largest QSRs run on AWS and what that actually means for how AI gets deployed at scale. Deborah breaks down the two stats dividing executive boardrooms right now, shares what it really takes to build the digital GM assistant every operator wants, and explains why the biggest obstacle for most restaurants isn't missing data but missing connectivity between systems.  The conversation goes deep on buy vs. build, data standards, and why so many AI pilots stall before reaching production. Deborah also draws on Amazon's own supply chain, Rufus, and Alexa Plus to illustrate what AI looks like when it actually earns consumer trust at scale, and closes with her full vision for the agentic restaurant: orchestrated AI agents handling supplier negotiations, inventory, GM-level decisions, and employee support all at once.  Whether you're a multi-unit operator figuring out where to start with AI, a restaurant tech executive weighing build vs. buy, or a founder designing a concept from the ground up, this episode gives you one of the clearest pictures yet of where the industry is heading and what separates the brands that will win.

Why Most Restaurant AI Is Just an If-Then Statement | Toby Malbec

In this episode of the Restaurant AI Podcast, host Matt Wampler, Co-Founder and CEO of ClearCOGS, sits down with Toby Malbec, a 30+ year restaurant technology veteran who has led technology strategy for brands including Church's Texas Chicken, Subway, and Saks Fifth Avenue. Known in the industry as an "operational technologist," Toby shares why most of what restaurants call AI is really just if-then statements, why the industry's fragmented tech stack remains its biggest obstacle, and what it actually takes to deploy technology inside the four walls. The conversation covers kiosks, drive-through voice AI, camera vision, and kitchen production, along with the real reasons these technologies succeed or fail in practice. Toby also dives into the franchise relationship, explaining how brands can collect and share data back to operators in a way that builds trust, and why the best technology decisions start with strategy, not a vendor pitch. Whether you're a franchise operator modernizing your tech stack, a technology leader navigating buy-versus-build decisions, or a restaurant executive evaluating AI solutions, this episode offers a candid, experienced perspective on what works and what's worth waiting for. Links: Connect with Toby Malbec on LinkedIn: 🔗 / toby-malbec-8989322 Connect with Matt Wampler on LinkedIn: 🔗 / matthewjwampler Learn more about ClearCOGS: https://www.clearcogs.com Chapters: 00:00 Intro & Coming Up 03:55 Welcome, Toby Malbec 05:07 What Is AI, Really? 06:44 Descriptive, Predictive & Prescriptive Analytics 10:11 Why Restaurant Data Doesn't Play Nice 14:15 AI Coding and Legacy Systems 18:19 Buy vs Build: Who Creates the Restaurant OS? 22:46 The Kiosk Debate 28:00 Drive-Through Voice AI 33:37 Evaluating Voice AI Vendors 38:46 Franchisees and Technology Decisions 44:31 Data Sharing and Franchisee Trust 51:52 Operational Efficiency in the Four Walls 57:35 Predictive Analytics That Work 1:01:13 How AI Changes the Restaurant Workforce 1:09:48 Advice on Deploying Technology 1:14:02 Where to Find Toby

Josh Kopel on AI, Systems, and Why Restaurants Must Evolve Now

In this episode of the Restaurant AI Podcast, host Matt Wampler, Co-Founder and CEO of ClearCOGS, sits down with Josh Kopel, restaurateur, coach, marketing strategist, and founder of the Restaurant Scaling System. Josh has built, scaled, and exited restaurants, including earning a Michelin star, but he’s blunt about what actually matters in this industry. From marketing myths to hiring systems powered by AI, this conversation dives into what separates restaurants that survive from those that scale. Josh shares why most restaurants are stuck in “performative marketing,” how to think differently about social media, why chasing awards won’t buy you freedom, and how AI can dramatically improve hiring and delegation. They also unpack the hard truth about industry consolidation, what “strategic ignorance” really means for owners, and why better questions, not more effort, unlock growth. Whether you’re an independent operator, founder, or scaling a multi-unit concept, this episode delivers sharp insights and practical frameworks you can apply immediately. Episode Links: Connect with Josh Kopel: https://joshkopel.com [https://joshkopel.com]Connect with Matt Wampler: https://www.linkedin.com/in/matthewjwampler [https://www.linkedin.com/in/matthewjwampler]Learn more about ClearCOGS: https://www.clearcogs.com [https://www.clearcogs.com] Chapters: 00:00 Intro & Coming Up 01:53 Welcome Josh Kopel 03:03 No Marketing → Performative Marketing → Effective Marketing 03:39 Why Social Media Is Low Intent 07:54 Why a Michelin Star Didn’t Create Freedom 09:43 “Do What You Think Is Cool” Philosophy 16:04 Using AI to Hire Better Employees 18:19 Hiring for Natural Predisposition 26:59 The Industry Reckoning: Top 30% Will Cannibalize 90% 52:34 Strategic Ignorance Explained 1:06:46 Why Knowledge Alone Isn’t Enough 1:07:26 Final Advice for Restaurant Owners

Aaron Knape: Computer Vision, Privacy, and the Next Leap in AI

In this episode of the Restaurant AI Podcast, host Matt Wampler, Co-Founder and CEO of ClearCOGS, sits down with Aaron Knape, Chief Revenue Officer at Amniscient, to unpack one of the most talked-about but least understood areas of AI: computer vision. While most AI conversations today focus on voice and text, Aaron explains why computer vision is different, and why it may be the missing layer that allows AI to finally understand the physical world. From grocery stores and restaurants to manufacturing and security, computer vision gives AI eyes, context, and ground truth data that language models alone can’t provide. Aaron breaks down what computer vision actually is, why it’s historically been so expensive and slow to adopt, and what’s finally changing. The conversation explores real-world use cases like self-checkout, inventory tracking, quality control, and operational visibility, along with the harder questions around privacy, data ownership, liability, and regulation. They also dive into the convergence of LLMs + computer vision, edge vs cloud processing, the future of robotics, deepfakes, and why adoption isn’t just a technology problem, it’s an education and implementation problem. Episode Links: * Connect with Aaron Knape on LinkedIn: https://www.linkedin.com/in/aaronknape/ [https://www.linkedin.com/in/aaronknape/] * Learn more about Amniscient: https://www.amniscient.com * Connect with Matt Wampler on LinkedIn: /matthewjwampler * Learn more about ClearCOGS: https://www.clearcogs.com Chapters + Timestamps 00:00 Intro & Coming Up 02:51 What Computer Vision Actually Is 04:15 CAPTCHA & Training AI 04:58 Why Computer Vision Stayed in Infancy 06:56 The “Autocomplete on Steroids” Moment 09:36 LLMs + Computer Vision: Giving AI Eyes 11:35 Why Video Hasn’t Delivered ROI Yet 13:17 Self-Checkout & Retail Use Cases 16:43 The SKU & Packaging Problem 19:35 Aaron’s Journey into Computer Vision 22:50 Cameras, 4K & Hardware Evolution 24:45 Edge vs Cloud Computing 29:47 Privacy, Data Ownership & Liability 35:00 Deepfakes & Regulation 41:58 The Risk of Too Much Visibility 46:18 AI, Education & The Next Generation 52:21 Where Computer Vision Is Headed 1:15:19 Final Thoughts & Where to Find Aaron