Tutor Intelligence has raised a $34M Series A to accelerate its vision of deploying low-cost, drop-in robots powered by fleet-scale learning. The company is demonstrating that real-world automation can expand rapidly when robots continuously learn from data generated in production environments. CEO and Co-Founder Josh Gruenstein highlights the full-stack nature of Tutor’s approach: combining hardware, software, and large-scale data collection to build a flywheel where more learning enables more robots, unlocking more data and delivering increasing customer value.



Tutor Intelligence, a robotics company redefining industrial automation through real-world learning and fleet-scale data, has announced a $34 million Series A financing led by Union Square Ventures (USV), with co-lead participation from Fundomo and continued support from seed investor Neo. This new round brings the company’s total funding to $42 million.

Building a Real-World Learning Flywheel

Tutor Intelligence was founded with a bold premise: robots should learn directly from real production environments—not simulated labs. The company deploys low-cost, drop-in robots that immediately contribute to factory operations while continuously improving through real-time human-in-the-loop tutoring and shared fleet intelligence.

Each robot collects high-value operational data during deployment. When encountering unfamiliar tasks, it can briefly request guidance from a remote human “tutor,” generating precise training examples that instantly improve the broader model. This approach creates a data flywheel:
more deployed robots → more real-world data → faster learning → higher autonomy → broader deployment.

From MIT Research to Nationwide Operations

Tutor’s founders, Josh Gruenstein and Alon, began as MIT robotics researchers fascinated not only by algorithms or hardware but by robotics as a full-stack systems challenge. They recognized early that the bottleneck in robot intelligence was not compute power—it was real-world data at scale. Traditional robotics projects struggled to collect enough of it; Tutor aims to solve this with a deployed nationwide fleet.

Today, Tutor robots operate across the U.S., supporting core production tasks for leading manufacturing and logistics companies. Their robots handle pick-and-place, assembly, packing, and other repetitive tasks, allowing operations teams to increase throughput while maintaining flexibility.

Funding to Scale Capability and Deployment

The newly raised capital will accelerate development in three areas:

• Faster autonomous learning, reducing the time from human-tutored behavior to stable autonomous execution.


• Expanded robotic capabilities, enabling more dexterous and intuitive manipulation across diverse industrial workflows.


• Broader fleet rollout, making advanced robotics accessible to mid-sized manufacturers that traditionally lacked automation resources.

A Team Built for Full-Stack Robotics

Tutor Intelligence now employs more than sixty team members across engineering, AI research, data operations, robotics technicians, and commercial functions. The company attributes its rapid progress to the alignment of all teams around a single mission: creating an abundant, affordable, software-defined workforce for the physical economy.

Co-founder and CEO Josh Gruenstein emphasized that the company is “just getting started,” highlighting the massive potential of real-world learning robots to reshape industrial productivity.

About Tutor Intelligence

Tutor Intelligence builds low-cost, rapidly deployable robots powered by fleet-scale learning. Its full-stack platform integrates hardware, AI, remote tutoring, and real-time data pipelines to deliver adaptive automation to factories and logistics facilities across the United States.