Vector Stream Systems logoVector Stream Systems
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The Single Source of Truth for Engineering Teams That Use AI

VectorOWL is the MBSE substrate that keeps your models, vectors, and constraints in one governed graph—so engineers, CI, and AI agents reason over the same structure.

The problem

When systems are tangled, risk is invisible

Cascading failures

One upstream change breaks downstream assumptions—and nobody sees it until integration.

Review bottlenecks

Traceability lives in slide decks and chat logs, not versioned structure engineers can diff.

Black-box decisions

AI agents draft code against stale or missing context—no URI, no log, no audit trail.

The solution

One graph. Three layers. Governed by default.

Graph

OWL reasoning gives your system formal, provable structure that survives scale and turnover.

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Vector

Semantic retrieval over simulations, telemetry, and documents—ranked by meaning, not keywords.

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Anchor

Hard constraints that override any probabilistic suggestion when safety or policy limits are hit.

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How it works

From model to deployment in three steps

1

Model in OWL

Assert structure, requirements, and relationships in a versioned ontology your team reviews like code.

2

Query with vectors + logic

Blend symbolic reasoning and semantic retrieval to find similar designs, anomalies, and gaps.

3

Deploy with anchors enforced

Hard constraints gate every release. Violations block merge—no silent drift into production.

Built for engineers

GraphRAG, natural language, and hybrid reasoning

vectorowl — bash
# Ingest unstructured requirements into the OWL graph
$ vectorowl ingest --source requirements.pdf \
  --ontology sysml-v2 --generate-edges
→ 142 requirements • 38 functions • 91 traces extracted

# Natural-language query — translated to SPARQL + vector retrieval
$ vectorowl ask "Which functions satisfy the energy-efficiency requirement?"
→ Function: optimize-fuel-injection (trace: REQ-042 → FUNC-17)
→ Subgraph: 4 nodes, 5 edges, anchor status: PASS

# Hybrid inference: symbolic entailment + vector similarity
$ vectorowl reason --alpha 0.7 \
  --from wing-design-v3 --to wing-design-v4
→ Symbolic consistency: PASS (OWL entailment)
→ Vector similarity: 0.89 (cosine, HNSW index)
→ Anchor gate: stress < 150MPa — PASS

# Register the MCP context server for Claude / Cursor
$ vectorowl-mcp --endpoint localhost:50051 --stdio

Framework

VectorOWL Architecture

vectorowl — architecture
┌─────────────────────────────────────────────────────────────┐
│                    CAD / CAE / PLM Tools                    │
│               (CATIA, Ansys, MATLAB, custom)                │
└──────────────────────┬──────────────────────────────────────┘
                       │ Model Context Protocol
                       ▼
┌─────────────────────────────────────────────────────────────┐
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐          │
│  │   Ontology  │  │   Vector    │  │   Anchor    │          │
│  │    Layer    │  │    Layer    │  │    Layer    │          │
│  │  OWL / RDF  │  │ HNSW / Faiss│  │  SMT / Rules│          │
│  │  SPARQL     │  │  Embeddings │  │  Constraints│          │
│  └─────────────┘  └─────────────┘  └─────────────┘          │
│         \                │                /                 │
│          \               │               /                  │
│           ▼              ▼              ▼                   │
│               ┌─────────────────────────────┐               │
│               │      Hybrid Reasoning       │               │
│               │   α · Symbolic + (1−α) ·    │               │
│               │      Vector Similarity      │               │
│               └─────────────────────────────┘               │
│                          │                                  │
│                          ▼                                  │
│               ┌─────────────────────────────┐               │
│               │   IdentityRegistry + DAG    │               │
│               │   ContextUpdate Events      │               │
│               └─────────────────────────────┘               │
└─────────────────────────┬───────────────────────────────────┘
                          │ gRPC / stdio
                          ▼
┌─────────────────────────────────────────────────────────────┐
│              MCP Hosts (Claude, Cursor, etc.)               │
└─────────────────────────────────────────────────────────────┘

The VectorOWL repository is currently private while we prepare the public release. You can get early access today by becoming a GitHub Sponsor — sponsors receive repo access, priority support, and direct input on the roadmap.

Sponsor on GitHub Try live demoView full framework

Use cases

Built for safety-critical domains

Aerospace

Reuse past wing configurations by semantic similarity while anchors enforce FAA structural margins. No design ships without proof.

Automotive

Embed fleet telemetry into the vector space. Anomalies near known failure modes trigger alerts before failure, not after.

Infrastructure

Model dependencies as a governed graph. When upstream constraints shift, see exactly which nodes and teams are impacted.

Pricing

Scale from prototype to production

Sponsor

Web instance. Community support.

$199/mo

Team

Cloud or private deploy. Priority support.

$399/mo

Enterprise

Custom SLA. On-prem. Dedicated engineer.

Contact us

Get early access

Start building with VectorOWL

Join the early access program. We'll reach out within 24 hours with next steps.