Autonomous · AI-native · No build required
VectorMBE
An MBSE substrate that connects your engineering tools into a governed knowledge graph. AI agents draft requirements, synthesize safety assessments, and trace change impact. Engineers review and approve every output.
U.S. Provisional Patent App. No. 64/073,689 — Patent Pending.
How it works
Three interlocking layers
Layer 1
OWL graph as the system of record
Every requirement, component, interface, and verification item is a node in an OWL knowledge graph. Relationships between them are formal and queryable. The graph is the single source of truth — tools feed it, they do not replace it.
Layer 2
Semantic retrieval across the graph
Each node is also indexed for meaning, enabling similarity search across requirements, simulation results, and test evidence. Find analogous past decisions, surface related constraints, and identify reuse opportunities by meaning rather than keyword.
Layer 3
MCP for tool coordination
The Model Context Protocol connects VectorMBE to your existing toolchain. Register the MCP server in Claude Desktop or Cursor and your AI assistant can read from and write to the governed graph. Changes propagate to connected tools automatically.
Capabilities
What VectorMBE does today
Requirements drafting
AI agents extract and draft formal requirements from source documents. Every requirement is linked to its source with full provenance. Engineers review and approve before anything is committed to the graph.
Safety assessment synthesis
Generate structured safety assessments from the graph. Failure modes, hazards, and mitigations are linked to the requirements and components they cover. The graph enforces constraint gates so safety-critical items cannot be bypassed.
Change impact tracing
When a requirement or component changes, the graph traversal identifies everything downstream: interfaces, tests, verification items, and affected safety assessments. Nothing falls through the cracks because the graph knows the dependencies.
Verification evidence tracking
Test results, inspection records, and analysis artifacts are attached to the requirements they verify. The graph surfaces open verification gaps and shows closure status across the program without manual status collection.
Text to CAD
Describe a system in plain language and the agent decomposes it into components and behaviors, each carrying a parametric envelope — dimensions expressed as expressions, not fixed numbers. VectorMBE emits those as OpenSCAD, a CadQuery script that writes STEP, or STL. Because the geometry comes through the governed model rather than straight from the prompt, every solid traces back to the requirement that drove it. If we can specify it, we can build it.
Hands-on
Connect via MCP
VectorMBE ships an MCP server, so Claude Desktop, Cursor and other MCP hosts can read from and write to the governed graph directly. Setup is a single config entry per host, and the current instructions live with the server itself rather than here, where they would drift.
Research foundation
Built on the DoD digital engineering standard
VectorMBE's architecture is grounded in the SERC Handbook on Digital Engineering with Ontologies v2.0, published by the Systems Engineering Research Center under the DoD Office of the Under Secretary of Defense for Research and Engineering. The handbook establishes formal ontologies as the semantic backbone for DoD digital engineering programs. VectorMBE applies those principles in a commercial platform.
Ready to connect your toolchain?
Talk to us about your program. We work with aerospace, automotive, defense, and infrastructure teams.