Northstar

For the past month, we've been quietly running pilots in homes in India. Now we're opening Northstar Services to the public. We believe the future of robotics should be built in real environments with real people, not just inside labs. Sign up below. northstarrobotics.ai/services/

Privacy is extremely important to us. Participation is fully optional. Recordings are focused only on specific tasks being performed, and we use safeguards such as facial blurring throughout the process.

Today, we're launching Northstar Services. We're offering free home services across the U.S., India, and Brazil. Cleaning. Organization. Yard work. Home maintenance. And more. Here's how it works ↓

We're cohosting the The Embodied Metal Hackathon! Happening Jul 17-19 in San Francisco's Mission. Three days, lots of robots, and the best hackers across Physical AI.🤖 Hosts and sponsors: @MissionRobotBay, @savant_vc, @NewTheoryAI, and @NorthstarRobots, with compute from @modal. Space is limited, so apply early: luma.com/embodied-metal

@KyleVedder We’ve been internally validating the data by fine-tuning policies including Pi 0.5 and MolmoAct2 on subsets of our egocentric + task-specific datasets. More on this soon!

@NorthstarRobots what policies did you train with your data? I can’t find any info about that on your website

Most robotics data is slop. That's the real bottleneck for physical AI. Bad angles. No diversity. No quality control. Impossible to train on. We raised $500K from Genius Ventures to fix this. Introducing Northstar.

@jonnbooth @kstonestudios 🧑‍🍳

@NorthstarRobots one of the better launch vids i've seen in a minute

Everything is data. But not all data is trainable. We're building the most high quality & trainable robotics dataset in the world. If you're working on robotics, request a sample today! We're also hiring: ML & software engineers (SF) and Operations (India, Brazil), email us contact@northstarrobotics.ai northstarrobotics.ai

But we don't just collect data. We make it trainable. Our pipeline handles filtering, segmentation, hand tracking, depth maps, multimodal sync, and human + auto annotations- so robotics teams don't have to. We've already validated performance improvements deploying our data on real robots. Labs get training-ready data out of the box.

Real-world egocentric data 🥒