Real-World Validation: Intelligent 3D Scene Composition in One Click
How our early proof of concept with SpaceForm Technologies revealed the urgent need - and huge opportunity - for true 3D spatial intelligence.
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[ Project Details ↓ ]
Proof of Concept with SpaceForm Technologies:
Proof of Concept with SpaceForm Technologies:
[ Overview ]
[ Overview ]
Spatial Intelligence’s journey began with a real-world problem...
Spatial Intelligence’s journey began with a real-world problem...
SpaceForm Technologies - a leader in 3D world generation for architecture visualisation - faced a major bottleneck:
SpaceForm Technologies - a leader in 3D world generation for architecture visualisation - faced a major bottleneck:
40% of their project time was spent manually selecting and positioning 3D assets - slowing delivery and constraining growth.
40% of their project time was spent manually selecting and positioning 3D assets - slowing delivery and constraining growth.
Scene composition - placing the right objects, in the right place, in the right way - was a critical pain point.
Scene composition - placing the right objects, in the right place, in the right way - was a critical pain point.
They needed intelligent automation to increase project throughput and scale their operations.
They needed intelligent automation to increase project throughput and scale their operations.
[ The Project ]
[ The Project ]
Over a six-month collaboration, we developed a single-prompt system that intelligently selected and positioned 3D assets - dramatically accelerating 3D scene composition.
Over a six-month collaboration, we developed a single-prompt system that intelligently selected and positioned 3D assets - dramatically accelerating 3D scene composition.
The system combined:
The system combined:
- Understanding of 3D assets (appearance, structure, function)
- Spatial context (scene geometry and layout)
- Creative intent (designer's high-level guidance)
- Common-sense relationships between objects (e.g., chairs around tables, lamps beside sofas)
In short, the system made decisions a human designer would - intelligently selecting and placing assets in a 3D environment with minimal input.
In short, the system made decisions a human designer would - intelligently selecting and placing assets in a 3D environment with minimal input.
[ The Results ]
[ The Results ]
- One-click intelligent scene composition
- Radically accelerated workflows
- Early validation of market demand for 3D spatial intelligence
[ The Limitation ]
[ The Limitation ]
While the proof of concept demonstrated real-world value, it also exposed the limits of existing 3D AI models and techniques.
While the proof of concept demonstrated real-world value, it also exposed the limits of existing 3D AI models and techniques.
Current vision-language AI models lack true spatial awareness and reasoning: the system could understand what objects looked like - but struggled to understand spaces and objects in 3D.
Current vision-language AI models lack true spatial awareness and reasoning: the system could understand what objects looked like - but struggled to understand spaces and objects in 3D.
[ The Opportunity ]
[ The Opportunity ]
This project validated a clear commercial need - and revealed an even bigger opportunity:
This project validated a clear commercial need - and revealed an even bigger opportunity:
To unlock the next generation of 3D automation and robotics, we need a foundational AI model built for end-to-end 3D understanding - not a patchwork of models trained for text or 2D images.
To unlock the next generation of 3D automation and robotics, we need a foundational AI model built for end-to-end 3D understanding - not a patchwork of models trained for text or 2D images.
Spatial Intelligence is building that model.
Spatial Intelligence is building that model.
We’re creating the core intelligence that understands the structure, content, and function of 3D environments - enabling machines to understand, construct, and interact with 3D spaces as humans do.
We’re creating the core intelligence that understands the structure, content, and function of 3D environments - enabling machines to understand, construct, and interact with 3D spaces as humans do.
We seek to unlock applications across architecture, gaming and robotics with a single, generalisable model, without the need for retraining.
We seek to unlock applications across architecture, gaming and robotics with a single, generalisable model, without the need for retraining.
This is just the first step!
This is just the first step!
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