Breaking
$450M Series A led by Premji Invest Valuation pegged at $1.7 Billion Out of stealth after 18 months FutureVision trains robots on internet-scale video Closed loop updates every few hundred ms Targeting a $30 trillion manual-labor market $450M Series A led by Premji Invest Valuation pegged at $1.7 Billion Out of stealth after 18 months FutureVision trains robots on internet-scale video Closed loop updates every few hundred ms Targeting a $30 trillion manual-labor market
Physical AI / Palo Alto, CA

Rhoda AI

The robots most companies show you work in a lab. Rhoda is building the ones that work where the boxes are crooked, the light is wrong, and nothing sits still.

Rhoda AI - Redefining Robotic Intelligence

RHODA AI. Two robot arms, a cardboard box, and a model that learned how the world moves by watching millions of videos. The whole pitch, in a single frame.

$450M
Series A
$1.7B
Valuation
~60
Employees
<2 min
Per work cycle
The Scene

On a factory floor somewhere in California, a pair of robot arms reaches for a cardboard box. The box is slightly out of place. The lighting has shifted since lunch. A human worker would not notice either thing - they would just adjust. For most robots, that small disorder is the end of the demo. For Rhoda's, it is just Tuesday.

That is the quiet, unglamorous problem Rhoda AI has decided to make its life's work: not the dancing humanoid that goes viral, but the dull, mission-critical motion that actually keeps manufacturing and logistics running. The company emerged from 18 months of stealth in March 2026 with a $450 million Series A, a $1.7 billion valuation, and a thesis that sounds almost too simple - teach robots the way the internet taught everything else. By watching.

We believe the next era of robotics requires models that understand how the world moves - not just what it looks like or how it's described in language.
— Jagdeep Singh, Co-founder & CEO
The Idea

Robots that read the future, not the manual

Most robots memorize. You show them a task, over and over, in a tidy lab. They get very good at that exact task and fall apart the moment reality wanders off-script.

Rhoda's bet is the opposite. Its system, FutureVision, is pre-trained on hundreds of millions of internet videos - so before it ever touches a real arm, it already has a rough physics of how objects fall, slide, bend, and bump. Rhoda calls the architecture a Direct Video Action (DVA) model: it watches a scene, predicts what happens next, and turns that prediction straight into motion. Then it does it again. And again. Every few hundred milliseconds, in a closed loop, the robot revises its next move as the world changes.

It is less "follow these instructions" and more "keep imagining the next second and act on it." The contrarian part isn't the ambition - it's the target. While the industry chases telegenic humanoids, Rhoda points its model at the work nobody films: the component-processing line, the box that has to move now.

01 / OBSERVE

Watch

Cameras feed a live view of the scene into the model.

02 / PREDICT

Imagine

FutureVision predicts the next states of the world on video.

03 / ACT

Move

DVA converts those predictions directly into robot actions.

04 / REPEAT

Adapt

The loop refreshes every few hundred ms as conditions shift.

The Math

A $30 trillion floor to sweep

Investor Mayfield framed the prize bluntly: the global market for manual labor runs around $30 trillion a year, with more than $10 trillion of it in the United States alone. You don't need to win much of that to matter.

The deployment math is just as direct. By Mayfield's estimate, roughly 1,000 deployed units would imply about $100M in recurring revenue; scale to 10,000 and you're looking at $1B+ ARR. Rhoda's longer game is to stop being only a robot company and start licensing its intelligence layer to other people's hardware.

The opportunity, in scale

Sources: Mayfield investment thesis, 2026
Global manual labor / yr$30T
US manual labor / yr$10T+
Rhoda Series A$450M
Post-money valuation$1.7B
The Build

Two names, one nervous system

Intelligence Layer

FutureVision

A foundation model built on video-predictive control. It carries long-context visual memory, predicts where a scene is heading, and runs the robot in a closed loop - revising actions every few hundred milliseconds. It powers Rhoda's own systems today and is meant to be licensed across other platforms over time.

Core Architecture

Direct Video Action (DVA)

The proprietary model that links perception straight to control. Pre-trained on internet-scale video for physics and motion priors, it converts predictions into real, physics-aware movement - and can pick up a new task from as little as ~10 hours of teleoperation data.

The People

A battery legend and two Stanford vision minds

CEO Jagdeep Singh is a serial deep-tech founder - best known for solid-state battery company QuantumScape - now pointing his track record at robot brains. Alongside him: the computer-vision research bench that makes the video approach plausible.

JS

Jagdeep Singh

CO-FOUNDER & CEO
EC

Eric Ryan Chan

CO-FOUNDER & CHIEF SCIENCE OFFICER
GW

Gordon Wetzstein

CO-FOUNDER · STANFORD IMAGING LAB
The Money

Who wrote the checks

A $450M Series A, led by Premji Invest, with a roster that reads like a deep-tech who's-who.

Premji Invest (lead) Khosla Ventures Temasek Capricorn Investment Group Mayfield John Doerr Leitmotif Matter Venture Partners Prelude Ventures Xora
The Story So Far

Short history, loud entrance

2024

Rhoda AI Corporation is founded and goes heads-down in stealth.

2024 – 2026 · STEALTH

18 months building FutureVision and the Direct Video Action model; quiet pilots in live manufacturing environments.

MARCH 2026

Exits stealth with a $450M Series A at a $1.7B valuation, led by Premji Invest. FutureVision unveiled publicly.

REPORTED

A component-processing workflow completed in under two minutes per cycle, autonomously - reportedly exceeding customer KPIs.

Margin Notes

Things worth knowing

The founder who once chased a better battery is now chasing a better robot. From QuantumScape to robot foundation models - across, by one account, roughly seven companies.

Instead of staged demos, Rhoda pre-trains on hundreds of millions of internet videos. The robot effectively learns physics by binge-watching.

The model "thinks" in a loop, rewriting its next move every few hundred milliseconds - closer to reflex than to a script.

The pitch is deliberately boring on purpose: skip the viral humanoids, automate the unglamorous work nobody films.

Back On The Floor

Return to that factory floor. The box is still slightly out of place. The light has still shifted.

The difference is that the disorder no longer ends the demo - it is the demo. Rhoda's arms reach, the box is handled, the cycle closes in under two minutes, and nobody calls a technician. If the company is right, the most important robots of the next decade won't be the ones doing backflips on a stage. They'll be the ones quietly handling the crooked box, in the wrong light, while the rest of us aren't watching - because they already watched everything else.

Watch

Interviews & demos