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Robotics / COMPANY INTELLIGENCE

Skild AI

Develops general-purpose AI models intended to control different robotic systems.

01 / THE BUSINESS

How Skild AI creates value.

Develops general-purpose AI models intended to control different robotic systems. The research focus is whether customer adoption can support attractive economics after development, delivery and ongoing service costs.

SectorRobotics
Founder coverage2 profiles
Research checkedSep 18, 2026

02 / PEOPLE BEHIND THE COMPANY

Meet the builders.

Co-founder

Deepak Pathak

Deepak Pathak is a co-founder of Skild AI. The company’s founding and leadership material provides context for its work in robotics foundation models.

Explore founder

Co-founder

Abhinav Gupta

Abhinav Gupta is a co-founder of Skild AI. The company’s founding and leadership material provides context for its work in robotics foundation models.

Explore founder

Selected 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.

What could work

The case to investigate

  • Whether a shared robotics brain can transfer across machines and environments.
  • A stronger product position becomes economically meaningful when customers renew, expand and pay enough to cover delivery costs.
What could go wrong

Pressure-test the thesis

  • Technical uncertainty.
  • Compute requirements.
  • Long commercialization horizon.

What to watch next

01

Cross-platform performance — what changed in the latest original disclosure?

02

Commercial integrations — what changed in the latest original disclosure?

03

Training-data advantage — 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.

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.