Robotics / COMPANY INTELLIGENCE
Physical Intelligence
Builds general-purpose AI systems for robots operating in the physical world.
01 / THE BUSINESS
How Physical Intelligence creates value.
Builds general-purpose AI systems for robots operating in the physical world. The research focus is whether customer adoption can support attractive economics after development, delivery and ongoing service costs.
02 / PEOPLE BEHIND THE COMPANY
Meet the builders.
Co-founder
Karol Hausman
Karol Hausman is a co-founder of Physical Intelligence. The company’s founding and leadership material provides context for its work in robotics foundation models.
Explore founder
Co-founder
Chelsea Finn
Chelsea Finn is a co-founder of Physical Intelligence. The company’s founding and leadership material provides context for its work in robotics foundation models.
Explore founder
Co-founder
Sergey Levine
Sergey Levine is a co-founder of Physical Intelligence. The company’s founding and leadership material provides context for its work in robotics foundation models.
Explore founderSelected founders; historical founding roles are distinct from current management positions.
03 / CAPITAL & OWNERSHIP
Follow the financing.
Selected disclosed events, newest first. Announcement values describe that transaction and date; they are not current share prices. Debt, equity and secondary transactions are identified separately.
A financing figure is not established here.
Use the original company sources below to check new announcements. We have not substituted an estimate for a disclosed round.
04 / IN THEIR OWN WORDS
Watch. Listen. Form your view.
A direct interview has not yet been verified for this profile. The company’s official materials are linked below.
Interviews reflect the speaker’s perspective at publication. Company statements are not independent verification.
05 / EDITORIAL ANALYSIS
The opportunity. The open questions.
Our interpretation of the business model and cited sources, not a valuation or a recommendation.
The case to investigate
- Generalization across tasks rather than narrow, separately programmed automation.
- A stronger product position becomes economically meaningful when customers renew, expand and pay enough to cover delivery costs.
Pressure-test the thesis
- Research-to-product gap.
- Data scarcity.
- Capital intensity.
What to watch next
Task generalization — what changed in the latest original disclosure?
Robot-platform coverage — what changed in the latest original disclosure?
Deployment partnerships — what changed in the latest original disclosure?
YOUR RESEARCH WORKSPACE
Keep the questions that matter.
Use this checklist to record what you have investigated. Your notes stay in this browser.
06 / RESEARCH TRAIL
Go straight to the source.
Company logo: original brand source. Trademarks identify their respective companies.
Research checked Sep 18, 2026. Selected public disclosures, not a complete capitalization table or securities-filing search. Missing information is left unconfirmed. No investment availability or IPO date is implied.
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