Chef Robotics

Chef robots can now handle meatpacking tasks 🥩 𝗪𝗵𝘆 𝗺𝗲𝗮𝘁𝗽𝗮𝗰𝗸𝗶𝗻𝗴 𝗶𝘀 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗶𝗻𝗴 𝘁𝗼 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗲 Unlike sauces or grains, raw meat cuts are irregular, deformable, and highly variable. Each piece differs in shape, weight, and texture depending on the cut and whether it is raw, frozen, or precooked. 𝗛𝗼𝘄 𝗖𝗵𝗲𝗳 𝗿𝗼𝗯𝗼𝘁𝘀 𝗵𝗮𝗻𝗱𝗹𝗲 𝗶𝘁 Chef robots automate meatpacking tray assembly tasks using our existing piece-picking capability. Our AI and computer vision system, trained on large volumes of data across protein types, enables our robots to: → Pick each piece at any angle from the pan and rotate it to the exact orientation required for each tray → Place items at defined offsets from the tray center for consistent, evenly spaced arrangements → Assemble multiple pieces of meat in the same tray in one go Chef robots can handle a wide variety of meat products like pork loin filets, chicken breasts, steaks, sausage links, and bratwursts. See how it works on our blog: chefrobotics.ai/post/chef-robo…

Today's customer spotlight highlights one of our very first customers: Chef Bombay. Based in Canada, Chef Bombay is an Indian meal manufacturer that brings high-quality, authentic Indian cuisine to kitchens across North America. After deploying Chef robots on their meal assembly lines, the team saw: 🥘 an 88% reduction in food giveaway ⚖️ a 30% improvement in consistency 🧑‍🍳 a 33% increase in labor productivity 📈 a 9% boost in throughput The 88% reduction in food giveaway has been particularly meaningful for Chef Bombay. At high production volumes, even small variations in portioning add up fast. Precise, consistent portioning for every serving can significantly impact yield and overall revenue. Thank you to the Chef Bombay team for the partnership! Read our in-depth case study to learn more: chefrobotics.ai/case-studies/c… #foodrobotics #foodmanufacturing #physicalai

Let's talk about burritos, wraps, sandwiches, and pizzas! 𝗪𝗵𝘆 𝗱𝗲𝗽𝗼𝘀𝗶𝘁𝗶𝗻𝗴 𝗼𝗻 𝗳𝗹𝗮𝘁𝗯𝗿𝗲𝗮𝗱𝘀 𝗶𝘀 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗶𝗻𝗴 Unlike trays or bowls, depositing ingredients onto flatbreads such as tortillas, wraps, lavash, naan, pita, sandwich bread, and pizza bases requires more precise detection and placement. This is because flatbreads lack fixed boundaries and depth, vary in shape and size, can be slightly folded or misaligned, and often blend visually with the conveyor. 𝗪𝗵𝗮𝘁 𝗳𝗼𝗼𝗱 𝗺𝗮𝗻𝘂𝗳𝗮𝗰𝘁𝘂𝗿𝗲𝗿𝘀 𝗱𝗲𝗮𝗹 𝘄𝗶𝘁𝗵 Without clear boundaries, robots need to determine each flatbread's footprint before placing ingredients. Flatbreads usually have larger surfaces, requiring the robot arm to travel further to place ingredients. In many cases, manufacturers need to increase conveyor speed to maintain throughput. 𝗛𝗼𝘄 𝗖𝗵𝗲𝗳 𝗿𝗼𝗯𝗼𝘁𝘀 𝗵𝗮𝗻𝗱𝗹𝗲 𝗳𝗹𝗮𝘁𝗯𝗿𝗲𝗮𝗱𝘀 Chef robots use AI-powered vision and camera-based perception to detect flatbreads in real time, identifying variable edges, texture, and shapes. We've trained our AI vision models on large-scale image and sensor data to generalize across different products and line conditions. Once Chef robots detect a flatbread, they place ingredients based on the required final product: • Linear placement for wraps and burritos • Centered placement for sandwiches • Distributed placement for pizza and flatbreads To maintain throughput, our robots dynamically adjust ingredient drop height (to control spread vs. concentration), end-effector motion (to match placement patterns such as point, line, or distributed placement), and timing and trajectory (to stay aligned with conveyor speed while minimizing spillage). 𝗧𝗵𝗲 𝗿𝗲𝘀𝘂𝗹𝘁 Food manufacturers can ensure consistent detection without missed flatbreads, precise placement without spillage, and reliable throughput across flatbread production lines—without modifying existing production infrastructure. Learn more: chefrobotics.ai/post/how-chef-… #foodmanufacturingUS #foodautomation #readymealmanufacturers #pizzaassembly

We're excited to welcome Vincent Benenati to our Robotics Software team! Vincent spent the last four years building robotics software for the restaurant industry at Bear Robotics. Now he's helping build the software and AI models that allow our robots to automate food manufacturing lines. If you're an engineer who's passionate about robotics and solving real-world problems, join us! See our open roles at chefrobotics.ai/careers #roboticsjobs #aijobs #hiring

Flashback to our demo at the All-In Summit last year! We showed what physical AI looks like in the real world. 🤖 Not a pitch deck, not a video, but a Chef robot assembling real food in real time. What summit attendees saw: → A Chef robot handling the unpredictability of real food ingredients → ChefOS adapting on the fly with real-time perception → Physical AI doing what traditional machines can't The US food manufacturing industry generates over $1T annually and relies heavily on manual labor. By automating complex, repetitive food assembly, our solution addresses these workforce challenges, freeing people up to focus on more valuable tasks. Thank you, All-In Podcast team, for having us! Interested in learning more? Let's connect: chefrobotics.ai/contact-us?utm… #PhysicalAI #Foodrobotics #Foodmanufacturing #allinsummit

Most food automation equipment is built around a simple assumption: if you control the ingredient, you control the output. That's why gravity-fed dispensers dominate the market. The core issue: food is inherently inconsistent. A chicken breast varies in size, weight, and shape. Roasted vegetables come in 12 different shapes on the same line. Shredded cheese often clumps together. Dispensers are built for a single ingredient, size, and speed, but in food manufacturing, constant variability leads to misportioning, line stoppages, and large-scale waste. This is exactly the problem physical AI is built to solve. Each Chef robot features three RGB-D cameras, a perception system, and a six-degree-of-freedom robotic arm to handle the inherent variability of food ingredients. These physical AI features ensure: → 𝗥𝗲𝗮𝗹-𝘁𝗶𝗺𝗲 𝗽𝗲𝗿𝗰𝗲𝗽𝘁𝗶𝗼𝗻: The robot sees food ingredients before it picks them up. → 𝗗𝘆𝗻𝗮𝗺𝗶𝗰 𝗮𝗱𝗷𝘂𝘀𝘁𝗺𝗲𝗻𝘁: It determines where to pick from and how to portion the ingredient accurately in real time. → 𝗙𝘂𝗹𝗹 𝗶𝗻𝗴𝗿𝗲𝗱𝗶𝗲𝗻𝘁 𝗰𝗼𝘃𝗲𝗿𝗮𝗴𝗲: The same robot can handle hundreds of ingredients, thousands of recipes, and endless portion sizes, regardless of size, texture, and temperature variations. Unlike traditional automation that demands uniformity, Chef robots enable food manufacturers to automate with flexibility, handling ingredients as they come while ensuring consistent portioning and precise placement. Hear more on The Front Lines podcast: frontlines.io/podcasts/rajat… #physicalai #robotics #computervision #foodmanufacturing

While many of us are familiar with software as a service (SaaS), robotics as a service (RaaS) is still a relatively new concept. With the emergence of physical AI, the way food manufacturers adopt automation is changing fast. Just as LLMs sparked a wave of AI software subscriptions, physical AI is doing the same for robotics. Today, the real differentiator isn't hardware; it's software and how quickly that software improves. A product that evolves continuously doesn't fit a one-time purchase model. RaaS is the natural result. Here's how food manufacturers can benefit from RaaS: → 𝗟𝗼𝘄𝗲𝗿 𝗿𝗶𝘀𝗸: Start small, prove value, and expand over time without a large upfront CapEx investment → 𝗙𝗮𝘀𝘁𝗲𝗿 𝗥𝗢𝗜: Deploy in days or weeks rather than months → 𝗙𝗹𝗲𝘅𝗶𝗯𝗹𝗲 𝗮𝗻𝗱 𝘀𝗰𝗮𝗹𝗮𝗯𝗹𝗲: Scale the number of robots with your needs, and reallocate them across lines and use cases → 𝗗𝗮𝗶𝗹𝘆 𝗶𝗺𝗽𝗿𝗼𝘃𝗲𝗺𝗲𝗻𝘁𝘀: RaaS companies are directly incentivized to maximize uptime and continuously improve the product → 𝗙𝘂𝘁𝘂𝗿𝗲-𝗽𝗿𝗼𝗼𝗳: As underlying AI models improve, customers automatically gain access to the latest features without having to repurchase hardware RaaS has been especially impactful for meal assembly, which has historically been too variable and high-mix for traditional machines to handle. Food manufacturers like Cafe Spice, Amy's Kitchen, and Chef Bombay are already seeing the results. Want to learn more about how RaaS is reshaping automation in food manufacturing? Read on our blog on this topic: chefrobotics.ai/post/what-is-r…

Please join us in welcoming Abhay Prithvi Komanduri to Chef's Robotics team! Abhay is joining us as a Robotics Software Engineer. With close to 5 years of robotics software experience from Dexterity and a Mechanical Engineering degree from @UW, Abhay will hit the ground running and help our growing team build and deploy AI-enabled robots that perform in challenging real-world production environments across North America. If this sounds like you, check out our careers page and apply for an open role: chefrobotics.ai/careers #robotics #ai #hiring

Introducing Robot-to-Robot (R2R) Communication 🤖 Food manufacturers who run high-speed lines often need more than one robot to serve the same ingredient on a shared conveyor. But two robots on the same line create a coordination problem: how do they agree, in real time, on which robot fills which tray? R2R communication solves this. It maximizes throughput while ensuring precise placement in every tray. Here's how it works: each Chef robot has a built-in wireless radio. The moment the first robot deposits into a tray, it immediately shares the tray's position and orientation with the next robot downstream. The next robot then knows exactly which tray to target and when to make its deposit. All our robots still run independent perception systems, so they stay robust to real-world variability. The result: → Easy to deploy without upgrading any infrastructure → Faster tray targeting and reaction time → Fewer errors like spillage or missed trays → Works across all ingredients without retraining or reconfiguration → Can be configured to run 150 trays per minute R2R communication is live at several of our customer sites. Read more on our blog: chefrobotics.ai/post/introduci… #foodmanufacturing #foodrobotics #AI #foodautomation #conveyorsystems

For decades, food manufacturing was considered "too hard to automate." The reason? Variability. → Ingredients differ in shape, size, texture, and orientation. → Tray compartments are often not uniform. → High-mix lines have constant changeovers. The reality on the line: Even small variations — an irregular compartment of a meal tray or inserts within a salad bowl that do not sit perfectly flat — can disrupt traditional automation. Physical AI, on the other hand, is built for exactly this. Chef robots are powered by ChefOS — our AI platform built specifically for food manufacturing. It uses deep-learning vision to perceive ingredients, bowls, compartments, and inserts in real time, and adapts to the variability that makes food so hard to handle. That means: → Robots that see and respond to real food, not idealized versions of it → AI that handles high-mix production without re-programming between SKUs → Systems that get smarter with every deposit The outcome: 90M+ servings made in production at customer facilities We were featured in Packaging Insights this week on exactly this shift — from rules-based automation to AI-enabled systems that can finally solve the challenges of food manufacturing. 🔗 packaginginsights.com/special-report… #physicalai #foodautomation #foodproductionandpackaging #roboticvisionsystems

We're thrilled to welcome Krishna Teja to Chef as a Senior Software Engineer on our Robotics Platform team! Before he joined Chef, Krishna spent five years at Dexterity as a Robotics Engineer. He's also conducted research at the University of Washington, where he earned his Master's degree in Mechanical Engineering. At Chef, Krishna will help build and deploy the platform and algorithms that power our robots, enabling our customers to assemble high-quality meals more efficiently and precisely across over a dozen production sites. Interested in working on real-world robotics deployed at scale? We're hiring across teams: chefrobotics.ai/careers #robotics #ai #hiring

We're excited to launch Conveyor Connect - enabling Chef robots to communicate with all types of food manufacturing conveyors! 𝗪𝗵𝘆 𝗰𝗼𝗻𝘃𝗲𝘆𝗼𝗿 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 𝗶𝘀 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗶𝗻𝗴 Food manufacturers use different pieces of automation equipment for different parts of their production lines, but integrating them can be challenging. Chef robots need to communicate with a manufacturer's conveyor system to perform well in production. 𝗧𝘆𝗽𝗲𝘀 𝗼𝗳 𝗰𝗼𝗻𝘃𝗲𝘆𝗼𝗿𝘀 Continuous belt conveyors run at a constant speed. In these cases, AI-driven perception is predominantly what Chef uses for detection of trays, detection of inserts of trays, tracking, speed estimation, anomaly detection, and general conveyor perception (i.e., what 3D plane is the conveyor on; how far away from the robot is it; is it skewed?). This allows us to handle the vast majority of edge cases, such as slanted conveyors, non-monotonic velocities and accelerations, most starts and stops, skewed conveyors, and randomness due to humans upstream and downstream. Indexing (stop-and-go) and chain conveyors require Chef robots to talk to the conveyor to ensure more reliable tray tracking and precise deposits. 𝗛𝗼𝘄 𝗼𝘂𝗿 𝗿𝗼𝗯𝗼𝘁𝘀 𝗰𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗲 𝘄𝗶𝘁𝗵 𝗰𝗼𝗻𝘃𝗲𝘆𝗼𝗿𝘀 𝘁𝗼 𝘂𝗻𝗹𝗼𝗰𝗸 𝘀𝘁𝗼𝗽-𝗮𝗻𝗱-𝗴𝗼 Our robots already use wireless radio systems to talk to one another. We decided to use the same technology for robot-to-conveyor communication as well. Our conveyor companion box - a small, waterproof electronics enclosure that attaches to the conveyor's VFD control system - contains a radio for direct communication between the conveyor and Chef robots. 𝗢𝘁𝗵𝗲𝗿 𝗯𝗲𝗻𝗲𝗳𝗶𝘁𝘀 In addition to enabling stop-and-go belts, for continuous belts, Conveyor connect can read and dynamically adjust conveyor speed to maximize throughput and minimize missed trays, deposit ingredients precisely onto conveyors while minimizing spillage, and react to sudden conveyor starts or stops without requiring any changes to existing line infrastructure. It also allows for better speed estimation for chain-link belts. One of our customers, Cafe Spice, is already using conveyor connect in production. Learn more about conveyor connect and how Cafe Spice is using it: chefrobotics.ai/post/introduci… #foodmanufacturing #foodautomation #foodproductionconveyors #conveyorsystems

How many Skittles per hour did this Chef robot deposit at @packexposhow East? 🍬 (Hint: It was a lot - share your best guess below!) Jokes aside, we had a great show last week and enjoyed showcasing our robot using a playful demo ingredient that drew a crowd. Skittles were a fun way to showcase the precision, consistency, and speed our robots deliver across fresh, cooked, and frozen ingredients in real production environments. Thanks to everyone who stopped by our booth and joined us at the Food Manufacturing Happy Hour! We look forward to exhibiting at several more shows this year. Next up: Food Northwest Process & Packaging Expo in Portland this April. Find us at Booth 709, or schedule time with our team here: chefrobotics.ai/events/food-no… #robotics #foodautomation #foodmanufacturing #packexpo #foodnorthwest

Our February newsletter is here! Read this edition to learn about: 🍱 Small compartments and inserts 🛍️ Piece picking from unstructured totes 🤝 Chef's partnership with Packline Solutions Group 🎪 A recap of PACK EXPO East 📖 Our complete guide to food manufacturing equipment Subscribe to receive every edition in your inbox: linkedin.com/pulse/february… #robotics #foodmanufacturing #foodautomation

We're excited to welcome Atharva Sonanis to Chef as a Robotics Applications Engineer! Atharva brings valuable robotics engineering experience from Fetch Robotics and Purdue University, where he worked as a Robotics & Systems Research Engineer in addition to his Master's degree in Mechatronics, Robotics, and Automation Engineering. At Chef, Atharva will work directly with our customers across the US and Canada to ensure our robots perform well in real-world production environments. Interested in the work our Robotics Applications Engineering team is doing? Apply to join our team: chefrobotics.ai/careers #robotics #ai #bayareajobs

Chef robots can now handle small compartments and inserts, and it's not as obvious as one might think 👇 𝗪𝗵𝘆 𝘀𝗺𝗮𝗹𝗹 𝗰𝗼𝗺𝗽𝗮𝗿𝘁𝗺𝗲𝗻𝘁𝘀 𝗮𝗻𝗱 𝗶𝗻𝘀𝗲𝗿𝘁𝘀 𝗮𝗿𝗲 𝗱𝗶𝗳𝗳𝗶𝗰𝘂𝗹𝘁 Many fresh or frozen prepared meal trays have 2-3 compartments or inserts with small cavities sitting on top of a larger bowl. This means smaller deposits and more challenging orientation and alignment during meal assembly, especially when inserts are tilted or rotated inside a bowl. 𝗪𝗵𝗮𝘁 𝗳𝗼𝗼𝗱 𝗺𝗮𝗻𝘂𝗳𝗮𝗰𝘁𝘂𝗿𝗲𝗿𝘀 𝘀𝘁𝗿𝘂𝗴𝗴𝗹𝗲 𝘄𝗶𝘁𝗵 𝘁𝗼𝗱𝗮𝘆 These tasks are notoriously hard to automate. Manufacturers need to staff their meal assembly lines with workers to perform the tedious job of scooping and placing incredibly small, precise amounts of food without spilling, while also working as fast as possible. 𝗛𝗼𝘄 𝗖𝗵𝗲𝗳 𝗿𝗼𝗯𝗼𝘁𝘀 𝗰𝗮𝗻 𝗵𝗮𝗻𝗱𝗹𝗲 𝘁𝗵𝗶𝘀 𝘁𝗮𝘀𝗸 We trained our robots on a lot of different types of trays and inserts, and we even designed a new, shielded utensil that minimizes spillage between cavities. The best way to learn how it all works is by reading our blog: chefrobotics.ai/post/small-com… #foodmanufacturing #foodautomation #robotics

Our Robotics team is growing, and we’re excited to welcome Berlin Paez to Chef as a Robotics Software Engineer. Berlin brings deep robotics and software experience from Saildrone, Bear Robotics, Amazon Lab126, and MIT Lincoln Laboratory. At Chef, he’ll help us build the software and AI models that power our meal assembly robots, enabling them to assemble millions of prepared meals for food manufacturers across the U.S. and Canada. Welcome to the team, Berlin!

We’re excited to welcome Sanjit Arunkumar to the team! He’s joining Chef as a Robotics Application Engineer, where he’ll work closely with our customers to deploy robots in real production environments. Before Chef, Sanjit worked on robotics integration at Amazon. With a Master’s degree in Robotics from the University of Illinois Urbana-Champaign and several prior roles in the field, he brings deep, hands-on experience to our applications engineering team. If Sanjit’s role sounds interesting, we’re growing the applications engineering team! Head to chefrobotics.ai/careers to apply and join us. #robotics #ai #hiring

Join us at our Food Industry Happy Hour in Philadelphia this month! During PACK EXPO East, we’re hosting an intimate gathering of food manufacturing professionals for drinks and light bites - an opportunity to connect with peers and discuss trends, challenges, and what’s next for the industry. 📅 Wednesday, February 18, 2026 🕔 5:00 - 7:00 PM ET 📍 Wilder (Philadelphia, PA) Apply to attend (limited spots available): luma.com/h9kiphn5 #packexpo #foodmanufacturing #foodautomation

We're heading to PACK EXPO East next month! If you're dealing with unfilled workstations on your food production lines or looking for ways to scale without adding headcount, come see what we're building. Our team will be at booth 930 with a live robot demo that shows how Chef robots handle real production challenges, from addressing labor gaps to increasing output by 2-3x. Stop by and meet Nick Yang, Jeff O'Neil, Charlotte Kosche, and Ethan Ashley to learn more about food automation powered by physical AI. See you in Philly! #PACKEXPOeast #manufacturing #foodautomation #foodproduction