Orbital Industries
Orbital Industries uses frontier AI agents to accelerate hardware invention by conducting sample‑efficient autoresearch and integrating robotic labs, dramatically reducing the number of physical experiments needed.
- Artificial Intelligence
- AI Agents
- Hardware
- Manufacturing / Industry 4.0
- New Materials
Funding
Raised to date
$50MRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
across 1 round
C+1$50M · Series B
Announced May 2026
Disclosed cumulative: $50M
Founders
Founder details are not available yet.
Product
Problem
Developing new physical products and manufacturing processes is costly and slow, requiring large, siloed R&D teams and lengthy, expensive experiments. This limits the ability to increase global production capacity and improve living standards, especially as labor forces shrink.
Solution
Orbital Industries applies frontier AI techniques to accelerate hardware invention and manufacturing. Its AI agents conduct autoresearch that identifies optimal designs and materials with far fewer physical experiments, reducing time and cost. By integrating robotic labs and AI-driven workflows, the company enables small, interdisciplinary teams to operate like software firms, rapidly iterating on product concepts. The platform has already generated novel molecular classes for high‑density GPU cooling and is intended to extend to energy, semiconductors, and other core industrial sectors, delivering better physical products at a fraction of traditional R&D expense.
Target Audience
Primary customers are industrial manufacturers, hardware R&D organizations, and emerging AI‑native hardware startups seeking to shorten development cycles and lower R&D costs.
Features
- Sample‑efficient AI autoresearch agents that converge on optimal designs in minimal physical trials
- Automated robotic laboratory integration for rapid, repeatable experimentation
- AI‑native workflow that structures hardware R&D as small, interdisciplinary, talent‑dense teams
- Generation of new material classes (e.g., high‑density GPU cooling compounds) through AI‑guided discovery
- Scalable platform architecture applicable to data centers, energy systems, semiconductors, and broader manufacturing