The wordmark is plain. The pitch isn't: that little "W" wants to read every camera you own.
It plugs into the CCTV you already bought and quietly asks the question managers keep forgetting to: is everyone actually doing the job?
FOSTER CITY, CALIFORNIA · FOUNDED 2017 · wobot.ai
Walk into any restaurant, warehouse, or store and look up. The cameras are already there - dozens of them, recording faithfully, understanding nothing. They are the most over-deployed and under-used sensor in modern business. Wobot AI exists because of that gap. The company takes the footage those cameras already produce and turns it into something a manager can act on before the lunch rush ends.
Today Wobot is a video-intelligence platform with roughly 110 people, an estimated $11.6M in revenue, and customers across food service, retail, manufacturing, hospitality, and pharma. It does not sell you a smarter camera. It sells the part everyone assumed the camera already had - the part that watches.
Here is the quietly absurd truth about running a multi-location operation: the rules are everywhere, and the checking is almost nowhere. A regional manager visits a store once a month, ticks a few boxes, and certifies that hands were washed, gloves were worn, the floor was mopped, the drive-thru moved fast - for the eleven minutes they happened to be standing there. The other 43,189 minutes run on faith.
Faith is expensive. A missed food-safety step becomes a health violation. A slow drive-thru becomes a car that drives off. A skipped procedure on a factory line becomes a recall. The cost of not knowing is real, but the cost of knowing - hiring humans to watch screens all day - was, until recently, worse.
The founders had stumbled into this before. Their earlier work was a mobile tool for running audits and inspections - clipboards, but digital. Useful, until they noticed the obvious flaw: an audit is a snapshot, and operations are a movie. What clients actually needed was continuous validation, not a periodic photograph of a good day.
Adit Chhabra (Purdue, then an MBA in Spain) had built that audit app and lived its limits firsthand. With co-founders Tapan Dixit and Tanay Dixit, he made a bet that sounds modest and turns out to be the whole game: the hardware problem was already solved. Cameras were cheap, ubiquitous, and pointed at exactly the things businesses cared about. The missing piece was software smart enough to turn pixels into "the 2 p.m. shift skipped a cleaning step."
The bet was attractive partly because it was so cheap for the customer. No rip-and-replace. No capital project. You keep the cameras, the wiring, the DVR in the back room - and Wobot's AI rides on top, reading the feed. In 2019 Titan Capital put in a seed round. In 2020, Sequoia India led a $2.5M pre-Series A through its Surge program. The investors weren't betting on cameras. They were betting that "the footage you already have is business intelligence you haven't read yet" was a sentence worth a company.
Wobot's platform is, mechanically, an AI-first SaaS that connects to existing CCTV and runs computer-vision models against the feed - often right at the edge, on hardware sitting in the store. What it does with that feed is the interesting part. It checks standard operating procedures against what actually happened on camera, and it does so continuously, which is the one thing a human auditor cannot.
Vision-based SOP and process compliance on your existing cameras, with real-time alerts, dashboards, and industry-specific checklists.
Real-time drive-thru speed-of-service metrics, so a bottleneck gets flagged during the rush, not in next month's report.
Tracks the full drive-thru path - entry queue, order point, pickup window, exit - to show exactly where the seconds leak.
Programmatic access to Wobot's object, activity, and event detection for teams that want the models in their own stack.
Yes, the drive-thru products are named ThruPut. Yes, that is both a pun and an actual metric. Engineers are allowed exactly one joke per product line.
Relative emphasis, not audited share. Food service is where a missed glove costs the most, so it's where Wobot leans hardest.
The proof isn't only revenue. It's who else builds on top of it. Interface Systems folded Wobot into a managed AI video-analytics offering for multi-location chains. Supermicro and AMD partnered to run Wobot's models at the edge for retail. Named customers include Goodwill, Ocean State Job Lot, and Mezeh. None of these are companies that adopt a camera-watching robot for fun - they adopt it because the alternative, not knowing, got too expensive.
Launched an AI-powered video analytics solution for multi-location businesses, built on Wobot's computer vision.
Collaboration to deliver retail AI at the edge - Wobot's analytics on Supermicro hardware with AMD compute.
Wobot's stated mission is to transform camera-system feeds into business intelligence - to make operational decision-making smarter across industries. Strip the polish off and it's a claim about waste: the world is drowning in video nobody reviews, and inside that video are answers to questions managers ask every day. Was the line too slow? Did the cleaning happen? Where did the customers actually go?
The mission has an ethical edge it doesn't dodge. Watching people work is a power, and Wobot leans on data privacy, video anonymization, and a SOC 2 posture to keep the watching about process, not about people. The point is the missed step, not the person who missed it.
The next move is bigger than counting cars. Wobot's recent direction - "fast everywhere," in its CEO's phrasing - points at multi-modal AI that reads the drive-thru and the dining room and the back-of-house as one continuous operation. As cameras get cheaper and edge compute gets stronger, the cost of understanding a feed keeps falling. The cost of not understanding it does not. That gap is the whole business, and it's widening in Wobot's favor.
The corner camera hasn't changed. It still hangs in the same spot, still records the same hours, still sees the same missed glove and the same slow car. What changed is that the footage no longer disappears unread into a drive in the back. Wobot AI made the most ignored sensor in business start answering questions - quietly, continuously, and without anyone having to stare at a screen. The camera was always watching. Now, finally, it's paying attention.