DISPELDA / SPATIAL INTELLIGENCE SYSTEMS
Intelligence for
the physical world.
DISPELDA develops the computational foundation that turns observations of real environments into coherent, persistent spatial models.
OUR FOUNDATION
A continuous model
of a changing world.
A single image is not a world model. Our architecture aligns observations, reconstructs geometry, connects places across time and preserves the evidence behind each spatial link.
THE DISPELDA ARCHITECTURE
From observation
to spatial memory.
Explore the foundations of a persistent world model.
Physical space becomes measurable.
Color, depth and timestamps provide complementary observations of an environment.
INTELLIGENCE, GROUNDED IN SPACE
AI informed by vision.
Grounded in geometry.
Visual AI identifies potentially related observations. Spatial verification tests whether those observations can credibly represent the same physical place.
Visual retrieval
A pretrained vision model proposes candidate revisits. Depth and camera-pose checks determine whether a spatial connection is supported.
World understanding
Persistent entities, semantic relationships and temporal reasoning are the next layers of the platform under development.
ENGINEERING DISCIPLINE
Built on evidence.
Designed for scale.
Geometric reconstruction
Depth-based acquisition, camera pose estimation and persistent geometry have been implemented and evaluated in engineering tests.
Spatial memory
Visual similarity proposes candidate revisits; geometric checks reject links that the available evidence does not support.
Semantic intelligence
Long-term object identity, semantic relationships and operational-scale deployment remain on the technology roadmap.
OUR VISION
A world model you can return to.
Our long-term direction is a spatial system able to answer what is present, what has changed and which observations support each conclusion.
Explore DISPELDA on GitHub ↗