Geometry becomes searchable reasoning context
Ask about surfaces, clearances, interfaces, envelope limits, or components without flattening the model into a document summary.
For manufacturing, agriculture, robotics, and design-heavy product teams
AI that understands a CAD model like a system, not a static file.
Move beyond text-only copilots. Give your teams answers grounded in assemblies, geometry, adjacency, and spatial intent so design, operations, and service decisions stay tied to the real product.
B-rep, meshes, drawings, metadata
Assembly relationships and topology
Grounded answers for design and field workflows
Why spatial context matters
Most CAD-heavy organizations already hold the answer inside the model.
Traditional AI reads filenames, notes, and fragments of text. Spatially-aware AI reads how the product is actually assembled, constrained, and used in the real world.
Assemblies stay connected to real dependencies
Keep part relationships, nesting, adjacency, and product structure intact so the model can reason with system-level awareness.
Answers become useful to executives and operators
Turn engineering context into faster quoting, review cycles, service prep, automation planning, and design-risk visibility.
The context layer
Spatial reasoning should deepen as the model moves from shape to action.
Geometry
Solids, surfaces, pockets, interfaces
Relationships
Assembly hierarchy, adjacency, motion constraints
Intent
Functional zones, maintenance access, manufacturability cues
Decisions
Answers you can route into engineering and operations
Scroll the workflow
Each stage adds more grounded context instead of hiding the geometry behind a text abstraction.
01
Parse the actual product structure
Ingest native CAD, drawings, and associated metadata without throwing away topology, dimensions, or assembly membership.
02
Preserve how components relate in space
Retain mating surfaces, adjacency, joint movement, and part dependencies so the model reasons at the system level.
03
Anchor geometry to engineering and field intent
Map surfaces and assemblies to maintenance zones, manufacturing constraints, robotic reach, or agronomic equipment behavior.
04
Return answers that stay explainable
Support design review, quoting, work instructions, and executive planning with reasoning that can be traced back to the model itself.
Where it lands
Built for teams where a wrong inference becomes a real-world cost.
Manufacturing
Help product, operations, and sourcing teams reason over tooling, serviceability, part substitutions, and design review bottlenecks with geometry still in view.
Agriculture
Connect implements, service assemblies, and field equipment logic so teams can move faster on maintenance planning, documentation, and product support.
Robotics
Ground AI responses in reach envelopes, collision-sensitive zones, actuator relationships, and packaging constraints across complex electromechanical systems.
Executive teams
Turn CAD intelligence into faster diligence, clearer design-risk conversations, and better visibility into how engineering context affects delivery and margins.
Start with one workflow
Show the team one assembly, one question, and one measurable gain.
A strong first pilot usually starts with a design review bottleneck, a service documentation gap, or a quoting workflow where spatial awareness changes the quality of the answer.