Integration in progress
One SDF path to the viewport
The Rust kernel, dependency graph and canonical SDF geometry underpin WebGPU/WGSL presentation. Production-path consolidation and hardware validation remain acceptance criteria.
AI-native CAD
for connected engineering.
Design in the browser with a Rust geometry kernel. NeuroCAD is connecting parametric modeling, model exchange and simulation through a shared engineering foundation, with canonical SDF geometry and WebGPU/WGSL presentation.
SDFCanonical geometryNative and imported bodies share the SDF presentation path.
WGSLProduction rendering directionWebGPU + WGSL, with hardware validation as the acceptance gate.
WASMWASM-NativeZero install. Runs in the browser.
EUEU-BasedBulgarian company. GDPR-native.
WHAT’S NEW IN NEUROCAD
From geometry to connected engineering.
October 2026 update. We are building a shared foundation for models, product revisions, computation and evidence. Here is what exists in code and where the platform is heading.
Core implemented
Products, revisions and assemblies
New domain models distinguish a part, an assembly, an immutable revision and a component occurrence. Geometry remains kernel-owned; integration across workbenches is ongoing.
Integration in progress
Exchange with the engineering world
STEP, IGES and mesh adapters provide the import/export foundation. REV13 develops exchange around semantic preservation, fidelity and provenance; support is validated for each format and model.
Core implemented
SageMath for symbolic mathematics
Symbolic operations have a dedicated SageMath integration. When configured, an unavailable SageMath service returns an explicit engine-labelled error. Geometry and interactive operations remain in the Rust kernel.
Core implemented
Reproducible engineering studies
The study domain model and API now bind study revisions to immutable engineering baselines. Computation engines are identified separately; complete solver workflows require their own validation.
REV13 direction
Editable models with traceable origins
Feature Program is the direction for versioned construction intent and dependencies. The goal is to trace a model change through computation, verification and results, with explicit validation in each workbench.
Pilots are scoped around a specific workflow. An implemented module or API does not establish a complete user journey; performance, fidelity and readiness are confirmed by executing that workflow.
Discuss your engineering workflowPLATFORM CAPABILITIES
Built as a platform.
Not a plugin.
Parametric and field modeling form the geometry foundation. Product revisions, engineering studies and exchange services extend the platform; workflow availability is confirmed during pilot scoping.
Sketch & Constraint Authoring
Deterministic constraint solver with canonical outcomes. Lines, arcs, circles, splines with geometric and dimensional constraints.
Feature Kernel
Implemented kernel paths for sketch-to-extrude and sketch-to-revolve, plus feature history and edit-intent infrastructure. Fillet/chamfer and richer feature workflows are being hardened for pilots.
Surface Modeling
Surface layer with NURBS admission/evaluation, loft/sweep execution contracts, surface session workflows, and quality/healing diagnostics. UI-level workflows are being productized.
Organic & Field Modeling
Field-native geometry with PDE-driven shape evolution. Sculpt, deform, and evolve surfaces with exact-zone protection.
Feature-Preserving Booleans
SDF booleans and smooth variants are implemented in kernel/session paths. Feature-preserving boolean reports and evidence exist, with integration hardening ongoing.
Diffusion & Evolution
Reaction-diffusion systems, mean curvature flow, Laplace-Beltrami operators. Bounded field evolution with replay safety.
Differentiable CAD
Gradient exposure for lawful geometry optimization. Sensitivities flow through the entire design graph.
Lattice Engineering
Graded lattice generation with parametric unit cells. Gyroid, diamond, octet — tuned for strength, weight, or thermal conductivity.
Material Fields
Continuous material grading from one zone to another. Per-voxel multi-material assignment for PolyJet and MJF printing.
Multi-Scale Composition
Macro structure + micro lattice + material grading, coordinated as a single design. Scales from millimeters to meters.
Manufacturing Governance
Manufacturing constraints are moving into governed design workflows. Wall thickness, draft, overhang, export, and validation evidence are tracked through deterministic gates.
Metrology & Inspection
Measurement, tolerancing, GD&T, QIF/DMIS, and inspection evidence loops for validation-driven engineering workflows.
TECHNOLOGY
Two mathematical engines.
One coherent CAD state.
DUAL MATHEMATICAL KERNEL
- Engine A: Signed Distance Fields and nalgebra/f64 evaluation for numeric geometry
- Engine B: Geometric Algebra in CGA + PGA for structure, transforms, and motors
- Dual-engine coherence checks compare Engine B projections against Engine A values
- E-graphs provide equality saturation and canonical-form extraction
- DCG, BVH, and NeuroGraph keep updates coherent across committed states
EXECUTION
- WASM compilation — kernel runs in the browser
- WebGPU + WGSL — canonical SDF presentation; hardware qualification ongoing
- Web Workers — kernel in background, UI always responsive
- Deterministic replay — every design reproducible from graph
- CRDT collaboration — real-time multi-user editing
MATHEMATICS
- PDE operators — reaction-diffusion, curvature flow, Laplace-Beltrami
- Adaptive field resolution — multi-scale refinement
- Differentiable geometry — gradients for optimization
- SageMath service integration — symbolic algebra and calculus with explicit engine identity
INTEGRATION
- MOOSE bridge — finite element simulation coupling
- STEP / IGES / mesh adapters — supported semantics and fidelity vary by format
- AI orchestration boundary — proposals validated, never source of truth
DUAL ENGINE ARCHITECTURE
SDF + GA, synchronized by graphs
Not only SDF. NeuroCAD has two complementary mathematical engines.
SDF/nalgebra owns numeric geometry; Geometric Algebra in CGA and PGA supports constructions and rigid motion. REV13 extends this foundation toward versioned feature programs and engineering traceability. Canonical SDF remains the presentation path for native and imported bodies.
ENGINE A
SDF numeric geometry
Signed Distance Fields and nalgebra/f64 evaluation provide the numeric geometry truth: inside/outside, distance, gradients, booleans, offsets, and field composition.
ENGINE B
Geometric Algebra CGA + PGA
CGA represents spheres, planes, circles, and tangent constructions. PGA represents rigid motion, screw axes, motors, mates, and mechanism paths.
COHERENCE
Projection and audit gates
Overlap operations are reconciled through projection π and per-operation tolerance ε. Engine disagreement is treated as a correctness signal, not hidden tolerance magic.
kernel_graphoperation history and canonical NodeId allocator
DCGdependency tracking and dirty propagation
e-graphequality saturation and canonical-form extraction
BVHspatial index for fast field queries
NeuroGraphdocumentary segmentation and history layer
COMPUTATIONAL PHYSICS & ENGINEERING COMPUTE
NeuroFEM.
From physics to verified engineering results.
NeuroFEM is the NeuroCAD computational-physics and engineering-compute domain. REV13 defines a solver-independent, method-independent, HPC-native architecture: formulate the physical problem, plan a qualified numerical method and backend, execute, and return traceable results.
Physics model and formulation
Fields, materials, loads, conditions and objectives feed the target Compute Model IR. Form-CAS and SageMath support formulation and symbolic verification through separate roles.
Numerical methods and solver backends
MOOSE provides bounded initial execution paths. Additional methods and MFEM/FEniCSx backends are architectural extensions requiring capability and qualification evidence.
HPC execution and traceable results
Compute Fabric separates placement from physics. The target ResultSet records the method, backend, inputs, artifacts, convergence, uncertainty and validation evidence.
HOW WE COMPARE
Not another CAD.
A different foundation.
| Capability | NeuroCAD | SolidWorks | Fusion 360 | nTop | Onshape |
|---|---|---|---|---|---|
| Implicit Geometry (SDF) | ✓ | — | — | ✓ | — |
| Parametric Sketching | ✓ | ✓ | ✓ | — | ✓ |
| Surface Modeling | ✓ | ✓ | ✓ | — | ✓ |
| Lattice Engineering | ✓ | — | — | ✓ | — |
| Differentiable CAD | ✓ | — | — | — | — |
| Browser-Native | ✓ | — | ~ | — | ✓ |
| WebGPU | ✓ | — | — | — | — |
| Deterministic Replay | ✓ | — | — | — | — |
| Material Fields | ✓ | — | — | ✓ | — |
| Manufacturing Governance | ✓ | ~ | ~ | — | — |
| AI Orchestration | ✓ | — | ~ | — | — |
| Simulation Bridge | ✓ | ~ | ✓ | — | — |
USE CASES
From aerospace to medical.
One platform.
Additive Manufacturing
- →Per-voxel multi-material assignment
- →Lattice grading for weight optimization
- →Conformal cooling channel design
- →4D printing of stimulus-responsive structures
- →Functional surface texturing
Aerospace
- →Structural topology optimization
- →Multi-scale composite design
- →Acoustic metamaterial panels
- →Thermal management geometry
- →Lightweight lattice wings
Medical Devices
- →Bio-inspired trabecular bone structures
- →Conformal fit from CT/MRI scans
- →Functional biocompatible surfaces
- →Multi-material gradient implants
- →Scan-to-CAD reconstruction
Automotive
- →NVH optimization with acoustic metamaterials
- →Conformal cooling for injection molding
- →Lightweight suspension components
- →Topology-optimized brackets
- →Manufacturing-aware geometry
Consumer Products
- →Organic form generation
- →Programmable mechanical properties
- →Topology optimization workflow setup
- →Procedural texturing for 3D printing
- →Multi-material soft/rigid zones
Energy & Sustainability
- →Heat exchanger optimization
- →Lattice structures for conductivity
- →Solar panel self-cleaning surfaces
- →Wind turbine blade internal lattice
- →Thermal energy harvesting devices
ROADMAP
Built in phases.
Validated with pilots.
R1 is the foundation layer. The investor story is the broader platform: pilot geometry, design intelligence, and industrial validation are already represented as tested kernel workflows under product hardening.
R1 — WORKING FOUNDATION
Core Geometry MVP
MVP LIVE- Sketching and constraints
- SDF primitives and booleans
- SDF field preview; meshing for downstream export
- STL export path
- Deterministic replay
R2 — PILOT GEOMETRY
Feature & Surface Kernel
PILOT FOCUS- Sketch extrude/revolve are live SDF features
- NURBS, loft, and sweep kernel paths are implemented
- Healing diagnostics and validation gates are in place
- Smooth SDF booleans are live, with feature-preserving evidence layers
- Surface-field conversion is moving through pilot hardening
R3 — DESIGN INTELLIGENCE
AI-Assisted Design & Optimization Workflows
TESTED FLOWS- Organic field modeling with protected exact-zone gates
- Gated diffusion / neural design operations
- Differentiable CAD signals for gradients, curvature, and SDF deltas
- Material fields with deterministic geometry coupling
- Multi-scale geometry composition across smooth SDF, morph/warp, and lattice fields
R4 — INDUSTRIALIZATION
Manufacturing & Validation
EVIDENCE GATES- Lattice engineering workflows with certification gates
- Metrology, GD&T, QIF/DMIS, and inspection evidence loops
- Manufacturing governance, BOM/PDM, and export readiness gates
- Topology optimization workflow scaffold under hardening
- TPMS, strut, Voronoi, plate, and neural lattice pattern libraries
PILOT ACCESS
Design partner access, not public SaaS pricing.
NeuroCAD is moving from MVP/demo toward focused pilot and design partner validation.
Demo Review
Intro/current path
Short technical and business review for investors, advisors, and potential design partners.
- ✓Working MVP/demo overview
- ✓Architecture walkthrough
- ✓Current status split
- ✓Pilot fit discussion
- ✓Follow-up materials
Design Partner
Pilot/qualified teams
Structured collaboration around one high-value workflow, with clear success criteria and evidence capture.
- ✓Workflow scoping
- ✓Pilot milestone plan
- ✓Geometry and export validation
- ✓Commercial feedback loop
- ✓Priority founder access
Enterprise / Strategic
Custom/by discussion
For industrial teams, strategic partners, and investors evaluating deeper technical collaboration.
- ✓Technical due-diligence session
- ✓Roadmap alignment
- ✓Security/IP discussion
- ✓Pilot or investment process
- ✓Legal review when needed
Discuss NeuroCAD as a pilot or investment opportunity.
Working MVP/demo available for qualified investor and design-partner conversations.