DEMIURGE builds Generative Immersive Virtual Models that create fully immersive training environments from a description — enriched with real-time physics and haptic feedback, for humans and robots alike.
Explore the vision ↓Just as large language models generate text, ideas, and code from a simple prompt, DEMIURGE's Generative Immersive Virtual Models (GIVM) generate complete virtual training environments from a description or a learning objective. Environments enriched with haptic and sensory feedback that make experience indistinguishable from reality — for trainees, surgeons, and autonomous robots.
We imagine a future where you describe a complex surgical procedure and our model creates — in seconds — an immersive, adaptive environment to train it.
The gold standard for realism, but costly, risky to patients, and entirely dependent on case availability. Cannot scale.
Good haptic realism, but limited scenario variability, high update costs, and only partially reusable. Static by nature.
Scalable and affordable, but low physical accuracy, no generative capability, and no automatic scenario customisation.
No existing platform combines AI-driven generation with real-time physics simulation. DEMIURGE fills this gap.
Every component is a research frontier. Together they form an integration no competitor currently offers.
Automatic creation of new immersive scenarios from text descriptions. Real-time simulation of complex physical phenomena.
Faithful real-time simulation of soft tissues, surgical instruments, and their interactions. Accurate enough to train both human surgeons and robotic systems.
Realistic perception of texture, stiffness, and reaction forces. Haptic data feeds back into model training for adaptive manipulation.
Augmented, virtual, extended, and mixed reality combined for multisensory, intuitive interaction without breaking immersion.
Privacy-preserving data sharing by design, using advanced cryptographic protocols. Enables sensitive clinical data to be used for model training without exposure.
Mechanisms designed to encourage cooperation between heterogeneous institutions — hospitals, universities, research centres.
Platforms like NVIDIA Isaac Sim and Unreal Engine excel at simulation. DEMIURGE is the only platform that integrates both — and adds haptics, secure data sharing, and cooperative incentives.
| Platform | AI Gen. | Physics Sim. | Haptics | Secure Data | Scalable Scenarios |
|---|---|---|---|---|---|
| DEMIURGE | ✓ | ✓ | ✓ | ✓ | ✓ |
| NVIDIA Isaac / Unity / Unreal | ✗ | ✓ | ~ | ✗ | ~ |
| Project Genie / NVIDIA Cosmos | ✓ | ✗ | ✗ | ✗ | ~ |
| Osso VR / PrecisionOS | ✗ | ~ | ~ | ✗ | ~ |
| Physical simulators (Simbionix) | ✗ | ~ | ✓ | ✗ | ✗ |
Integrate first generative features into the existing VR prototype. Validate business model hypotheses. Conduct patentability study. Funded by Sapienza grant.
Deliver the Simulator Core to the first early adopter — Policlinico Umberto I or Gemelli. Validate the technical support and clinical training model.
Activate annual service and update streams. Expand into synthetic dataset sales for surgical robotics R&D.
Scale the GIVM engine to biology, chemistry, industrial manufacturing, and complex robotics. Position DEMIURGE at the frontier of physical agentic AI.
Internationally recognised expertise in AI, physics simulation, cryptography, and game theory.
Startup experience; WSENSE co-founder. Bridges academic research and market.
Data sharing incentives and institutional cooperation. Industry experience with Google.
Built the first DEMIURGE demonstrator. Expert in dynamic systems and medical robotics.
Automatic creation of immersive modules. Industry collaboration with Google and Meta.
Designs secure, confidential protocols for multi-institution data sharing.
Physics modeling and immersive systems applied to robotic surgery.
FAIR Research Fellow. Implements complex physics simulations in real time.
Topological machine learning and physics modeling applied to medicine.
Distributed ledgers and advanced cryptographic tools for data governance.
We are looking for early adopters, research partners, and investors who want to be part of building the generative engine for immersive virtual worlds.