Gravis Robotics
An ETH Zurich spinout developing software, sensors and control systems for excavators and other construction equipment.
Europe's most interesting startup stories. Every week.
No spam. Unsubscribe anytime.
Podcast Episode
🎙️ Deep Dive
EP64 — Ecosystem Spotlight — August 2026: Europe moves from funding rounds to the test of scale
Listen to the episodeAbout Gravis Robotics
Gravis Robotics combines 3D perception, planning, autonomous control and teleoperation to make construction machinery programmable. It pursues staged autonomy, beginning with operator assistance and repeatable tasks before extending automation.
The Story
Founded in 2022 as a spinout from ETH Zurich’s Robotic Systems Lab.
How Gravis Robotics works
Business Model
Integrated B2B technology sold with and to heavy-machinery manufacturers and operators.
Revenue Model
Software licences, integration and potential hardware-as-a-service models; commercial terms are undisclosed.
Products & Services
Key Products
- Autonomy stack for heavy machinery
- 3D operator-assistance system
Core Use Cases
- Autonomous excavation
- Earthmoving
- Teleoperation
- 3D operator assistance
Market & Clients
Key Customers
Construction firms, heavy-machinery operators, OEM manufacturers and major infrastructure projects.
Geographic Presence
How Gravis Robotics competes
Competitors
Competitive Advantages
- Research originating from ETH Zurich
- Integration with existing heavy machinery
- Staged path from assistance to autonomy
How Gravis Robotics grows
Growth Strategy
Grow the team, expand international deployments and increase the number of supported autonomous tasks.
Distribution Model
Direct sales and partnerships with OEMs, contractors and fleet operators.
Moat (Defensibility)
Robotic control expertise, jobsite operating data, machine integrations and earthmoving know-how.
Regulatory Context
Workplace safety, product liability, machinery certification and industrial-automation rules all shape distribution.
Key Risks
- Safety in unstructured environments
- Liability for incidents
- Long industrial sales cycles
- Integration across heterogeneous machinery
- Gap between demos and sustained reliability
Strategic Insights
- A staged path from assistance to autonomy may reduce adoption friction.
- Data collected on real jobsites can become a cumulative advantage.
Funding & Investors
Funding Rounds
- 2026 - Series A: $200M
Lead: SoftBank
Key Investors
Founding Team
Founders
Key Metrics
Lessons from Gravis Robotics
- Physical AI needs reliability measured in operating hours rather than demos.
- Integrating with existing hardware may accelerate distribution compared with building a complete machine.
Similar Startups
Giotto.ai
Italian AI startup applying machine learning to optimize manufacturing processes and supply chains for industrial enterprises.
Read AnalysisANYbotics
ANYbotics develops quadruped autonomous robots for industrial inspection in complex environments, selling not just hardware but an operating layer for digitizing maintenance and data collection.
Read AnalysisMosaic SoC
Mosaic SoC designs low-power perception chips for spatial intelligence on mobile, AR and wearable devices.
Read Analysis