The company teaching factory cameras to see food the way a person does - and catch what humans miss.
Oxipital AI builds AI-enabled machine vision systems for the messy, high-variability world of food and consumer-goods manufacturing. Its cameras and software watch products move down a production line, then decide - in real time - whether each one passes, needs picking, or should be pulled for a defect or a foreign object.
The company sits at the intersection of computer vision and industrial automation. Where a traditional vision system needs painstaking rules and controlled conditions, Oxipital AI's approach is designed to handle the natural variation of real food: a chicken breast, a slice of produce, a frozen pizza. The pitch is deceptively plain - "AI Vision Made Simple" - but the underlying job is one the industry has struggled with for decades.
Oxipital AI is not a fresh startup. It began in 2012 as Soft Robotics, a Bedford company known for squishy, food-safe robotic grippers. In 2024 it sold that hardware business to the Schmalz Group and rebranded around the technology it had quietly been building since 2016: machine vision. The new name pays homage to the occipital lobe, the visual-processing center of the human brain.
An integrated, no-code AI vision platform that lets manufacturers and machine builders deploy and scale inspection, foreign-object detection, yield and throughput optimization, and vision-guided robotics - with synthetic data generation, pre-trained object models, web dashboards and production analytics.
Compact, food-grade IP69K vision hardware for high-speed inspection and robotic picking. Smaller, more powerful and lower cost than its predecessor - built to survive the pressure-washed, high-temperature reality of a food plant. Launched at PACK EXPO.
Applications for defect detection and classification, product-attribute measurement, foreign-material detection and quality control across food, produce, poultry, meat, bakery and consumer packaged goods.
Factories have automated motion, sorting and packaging for years. What they've struggled to automate is judgment - the ability to look at a product that is never quite the same twice and decide what it is and whether it's good. That gap has real costs: missed defects, food-safety risks, wasted yield, and labor spent on repetitive visual checks.
"Machine vision has historically been one of the largest failure points in industrial automation. Oxipital AI has built a fundamentally differentiated approach that is already proving itself in production at scale."
Two choices set Oxipital AI apart from classic machine-vision vendors. First, it leans on synthetic data - generating training images rather than collecting and labeling thousands of real ones - so a line can get an inspection model without months of manual work. Second, V-CORTX is built as a no-code platform with pre-trained object models and web dashboards, aimed at plant teams rather than vision PhDs.
The company frames this as "deep object understanding" in service of Industry 5.0: giving conventional automation the ability to observe, understand and act in complex environments. Where incumbents like Cognex and Keyence built the machine-vision category on rules and controlled lighting, Oxipital AI is betting the future belongs to adaptable, AI-native systems that tolerate variability.
"The VX2 is the result of that philosophy in action. It's smaller, more powerful, and more versatile, enabling customers to build more resilient manufacturing processes."
Oxipital AI sells B2B to food and consumer-goods manufacturers and to the machine builders who integrate its systems. Its market is the vision layer of modern food production - a slice of industrial automation being reshaped by labor shortages, tightening food-safety expectations and pressure on yield. A recent production contract covers 120 vision systems for foreign-object detection across multiple lines and facilities.
Notably, some of its investors are also its customers: Tyson and Johnsonville both backed the company and operate in the plants Oxipital AI aims to serve.
The 2022 Series C brought $26M from strategic backers including Tyson Ventures and Johnsonville Ventures. In July 2026, after the rebrand and rapid V-CORTX adoption, the company closed a fresh Series A co-led by SAS Private Equities and Scale Venture Partners, with Material Impact participating.
"Food manufacturing is entering a new era... our V-CORTX platform changes the game, enabling conventional automation systems to observe, understand, and act with human-level performance in complex real-world environments."
Launches in Bedford, Massachusetts, pioneering food-safe soft robotic grippers.
Core AI machine-vision technology is developed under the Soft Robotics umbrella.
Raises Series C from strategic investors including Tyson Ventures and Johnsonville Ventures.
Sells its gripper hardware business to Schmalz and rebrands around machine vision.
Unveils the compact, food-grade VX2 Vision System and is named a technology-excellence awards finalist.
Closes a Series A led by SAS Private Equities and Scale Venture Partners while tracking 400% revenue growth.
The name "Oxipital" nods to the occipital lobe - the visual-processing center of the human brain.
It sold the very business it was founded on (soft grippers) to become a vision company.
VX2 cameras carry an IP69K rating - they survive high-pressure, high-temperature wash-downs.
Its models train partly on synthetic data, sidestepping months of hand-labeling.
Two investors - Tyson and Johnsonville - are also customers.
It builds AI-powered machine vision systems - the V-CORTX platform and VX2 hardware - for quality inspection, foreign-object detection, yield optimization and vision-guided robotics in food and consumer-goods manufacturing.
Yes. Soft Robotics rebranded as Oxipital AI in 2024 after selling its gripper hardware business to the Schmalz Group and focusing entirely on machine vision.
Mark J. Chiappetta is the President and CEO.
It is headquartered at 32 Crosby Drive, Bedford, Massachusetts, in the Greater Boston area.
Roughly $84 million total, including a $26M Series C and a 2026 Series A co-led by SAS Private Equities and Scale Venture Partners.