Tutor Intelligence, an AI-powered fleet of warehouse robot workers, has announced the close of its $34 million Series A led by Union Square Ventures, bringing the company’s total capital raised to $42 million.
With the new capital, the company will accelerate the commercialization of its state-of-the-art robots, scale its consumer packaged goods fleet, and advance its central robot intelligence platform and research infrastructure to power a suite of new robot form factors and capabilities.
In addition to Union Square Ventures, known for its investments in Twitter, Coinbase, Etsy, and MongoDB; Fundomo, backers of Standard Nuclear, Mercor, Etched, and Atomic Semi, also participated in the round, along with follow-on investment from Neo, which led Tutor’s seed round and has invested in Cursor and Kalshi.
Rebecca Kaden, managing partner at Union Square Ventures, says: “Tutor stands out for its extraordinary speed of execution and its ability to balance cutting-edge product and model development with a clear commercial focus that quickly gets this functionality into customers’ hands.
“They’re not building for an abstract future; they’re transforming how CPG companies operate today. The team is super fast and ambitious, and we’re thrilled to lead this financing.”
Founded out of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), Tutor Intelligence has built the data engine powering fleets of robots that move North America’s consumer packaged goods.
This centralized intelligence system is changing robotic capability and applicability in manufacturing and logistics environments, logging tens of thousands of hours of real-world production experience that is continually reinvested to make the robots smarter, faster, and easier to use.
The company’s robots work alongside human operators to process items for a vast Fortune 50 supply chain network, multiple Fortune 500 packaged food companies, and category-defining global leaders across personal care, toys, home goods, beauty, and consumer technology.
Josh Gruenstein, co-founder and CEO of Tutor Intelligence, says: “When we started Tutor Intelligence nearly five years ago as grad students at MIT, we saw that the robotics intelligence bottleneck was the key barrier to robotic worker viability.
“We built a system that leverages on-the-job data to teach robots to navigate and understand the physical world with human-like intuition. This new capital enables us to expand our fleet, scale our robot training infrastructure, and empower our robots to tackle increasingly complex tasks, reshaping industrial work as we know it.”
Tutor robots use advanced visual intelligence to identify, adapt to, and handle virtually any SKU in live production. Unlike traditional robots that are pre-programmed to perform narrowly defined tasks in tightly controlled environments, Tutor robots can tolerate the imperfect realities and edge cases that define real-world operations.
While other models are trained on simulated or synthetically-generated data, Tutor’s fleet collects rich visual motor data from performing tasks in the field. This real-world data is then collated to train better AI models, improving the product and the robots’ capabilities over time.
Tutor’s systems are delivered to customer sites just 30 days after signing, are typically fully operational just one day after delivery, and can be funded entirely from a company’s operating budget through a Robot-as-a-Service (RaaS) subscription-based model that mirrors traditional labor costs.
By merging the best of automation with the accessibility of labor, co-packers, manufacturers, and third-party logistics (3PL) providers gain the reliability, efficiency, and cost advantages of advanced automation, without taking on the burden of ownership, maintenance, technical staffing, or long ROI timelines.
