Stanhope AI
About
About Stanhope AI
Stanhope's Free Energy Minimizing world model combines predictions about the environment with incoming sensor information and a goal for the machine. Its planning process balances actions that gather useful information with actions that advance the task. The model exposes internal beliefs and reasoning, allowing people to examine how the system selected an action.
The company demonstrated this architecture on drones carrying out three real-world missions, using the model for behaviour control and flexible mission planning with human-machine interaction. Its broader software work targets on-device operation and integration with conventional computer-vision systems, bringing the decision-making model into autonomous machines with limited onboard power and computing resources.
Funding
- 2026-02-12 - Seed - $8M - Stanhope AI raises EUR6.7M seed round for adaptive AI
Stanhope AI update detected via RSS; sources scraped for verification. - source: stanhopeai.com
- 2024-03-20 - Seed - $2.7M - Stanhope AI raises £2.3 million to advance neuroscience-inspired AI for autonomous machines
source: tech.eu
Investors
- Angel investors - Participant - Angel / Individual - 1 funding event - first seen 2024-03-20
- Auxxo Female Catalyst Fund - Participant - VC - 1 funding event - first seen 2026-02-12
- Frontline Ventures - Lead - VC - 1 funding event - first seen 2026-02-12
- MMC Ventures - Participant - VC - 1 funding event - first seen 2026-02-12
- Moonfire Ventures - Participant - VC - 1 funding event - first seen 2024-03-20
- Paladin Capital Group - Participant - VC - 1 funding event - first seen 2026-02-12
- Rockmount Capital - Participant - VC - 1 funding event - first seen 2024-03-20
- UCL Tech Fund - Lead - VC - 1 funding event - first seen 2024-03-20
- UCL Technology Fund - Participant - VC - 1 funding event - first seen 2026-02-12
Team
- Kimberley Stachenfeld - Co-Founder and CEO - Leads Stanhope AI's commercial translation of active inference into adaptive control for autonomous physical systems.
- Rosalyn Moran - Co-Founder - Co-founded Stanhope AI to translate active-inference and Free Energy Principle research into adaptive machine intelligence.
- Karl Friston - Co-Founder and Scientific Adviser - Provides the scientific foundation for Stanhope AI's active-inference approach to adaptive machine control.
Timeline
Events
- 2026-02-12 - Funding - Stanhope AI raises EUR6.7M seed round for adaptive AI
Stanhope AI raised EUR6.7 million ($8 million) in seed funding. The round was led by Frontline Ventures with participation from Paladin Capital Group, Auxxo Female Catalyst Fund, UCL Technology Fund, and MMC Ventures. The company said the capital will support adaptive AI for robotics, drones, autonomous vehicles, and defence systems.
Source - 2024-03-20 - Funding - Stanhope AI raises £2.3 million to advance neuroscience-inspired AI for autonomous machines
Stanhope AI previously raised £2.3 million in an earlier funding round The company positioned the round around agentic AI inspired by neuroscience for real-world autonomous decision-making UCL Business highlighted the financing as a milestone for the spinout's commercialization path
Source
Relations
Relationships
- SPRIN-D
Partner - Stanhope AI and SPRIN-D partnered on a year-long delivery-drone program for challenging scenarios.
Context
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Shared workflows
- DexForce
workflow adjacency - Embodied World Model Training
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workflow adjacency - Embodied World Model Training
- Aether AI
workflow adjacency - Embodied World Model Training
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workflow adjacency - Embodied World Model Training
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workflow adjacency - Embodied World Model Training
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workflow adjacency - Embodied World Model Training
- XIRRA
workflow adjacency - Embodied World Model Training
- Reactor
workflow adjacency - Embodied World Model Training
Context tags
- Active inference autonomy software - Peer Group
- Active inference robot control - Workflow
- Brain-inspired autonomy - Capability
- Active inference software layer - Stack Layer
- Embodied world model training - Workflow
- Robot model supply chain - Customer Environment
- Robot-learning infrastructure stack - Stack Layer