Engineering knowledge unification
Unify PLM, ALM, ERP, CAD, and document artifacts into a single governed context layer that engineers and AI agents query from one place.
Platform · Data Context Hub
Data Context Hub builds your engineering context layer.
Connect engineering data, model your domain ontology, build a governed context graph, and retrieve precise context on demand — for engineers and AI agents alike.
DCH · context graph
context retrieved
requirements12 linked
tests24 evidenced
lineagev3 → v4
gates2 pending
IntakeOntologyContext GraphRetrievalVersioningGovernance
01 — How DCH works
From raw artifacts to governed context.
Connect source systems through intake agents — PLM, CAD, ERP, requirements, any engineering data.
- Read-only ingestion where compliance requires
- Inherits source-system ACLs by default
- Continuous sync via change-data capture
Components, requirements, test results, change requests — typed and related, no code.
- No-code entity + relationship modeling
- Business rules and validation inline
- Versioned, governed, and auditable
Every entity, relationship, and attribute carries provenance and lineage.
- 1.4M+ entities and 8.7M+ edges at scale
- Stable cross-system identity per record
- Provenance + revision history on every fact
Engineers see only what their role and program permits.
- Role-based and attribute-based access
- Program-level tenant isolation
- Full audit trail on every action
Query and traverse the graph for AI agents, search tools, and workflows.
- Linked Data API, GraphQL, and MCP
- Median query: 128 ms across 1.4M nodes
- Every result traces back to source
02 — Inside DCH
The real product, not a concept.
DCH · Ontology Builder
DCH · Graph Explorer
03 — Use cases
Where DCH earns its place.
04 — Enterprise grade
Built for regulated engineering.
DeploymentOn-prem · VPC · EU-sovereign cloud
GovernanceRole-, attribute-, and program-level ACL
ComplianceTISAX Level 2, GDPR, ISO 27001
AuditFull lineage, versioned, tamper-evident
Unify your engineering context.
Connect your systems, model the ontology, and build a governed context graph your teams and agents can trust.
DCH turns fragmented engineering data across PLM, ALM, ERP, CAD, requirements, FMEA, documents and data lakes into one governed knowledge graph that every team and AI agent can query.
DCH · The Context EngineSYNCED · 1.4M NODES · 8.7M EDGES
Sources connected8
Entities in graph1.4M
Edges8.7M
Median query128ms
01How DCH works · five stages, one fabric
From fragmented sources to retrievable context.
Each step builds on the last. Connect sources, model your ontology, instantiate the graph, govern it, then retrieve precise context on demand. Click through the steps below.
Connect every engineering source.
Connect source systems through intake agents. PLM, CAD, ERP, requirements — any engineering data source.
- Read-only ingestion where compliance requires it
- Inherits source-system ACLs by default
- Continuous sync via change-data capture
02Model your ontology · no code
Engineers model the domain directly. No code.
No graph database experts. No hard-coded logic. Entities, relationships, and business rules are defined by the people who understand the data.
Entities & relationships, visual
Draw the entity model directly on canvas — Part, Requirement, Test, Material — and connect them with named, governed edges.
Business rules inline
Constraints, validations, derivations — defined where they belong, on the model, not buried in a service layer.
Isolated subsets, focused work
Select target entities and isolate just the subgraph you care about — model the powertrain ontology without seeing the whole company.
DCH· Ontology BuilderLIVE
03Explore · the living knowledge graph
Explore your knowledge graph.
DCH instantiates the ontology into a living, governed graph across source systems. Navigate visually — or query precise context for every engineering question.
DCH· Graph ExplorerLIVE
04DCH in action · the real product
See the full product.
From source system to governed graph, DCH is a full engineering context platform — not a database tool. This is what it looks like in production.
🔒app.context64.ai/dch/build
CONNECTED
05Use cases · built for engineering
Where DCH delivers value.
From unifying fragmented data to powering AI reasoning, DCH is the context backbone for engineering organizations.
Compliance & evidence trails
Automatically assemble evidence packs for ISO 26262, TISAX, and internal audits — every relationship is versioned and traceable.
AI-ready context retrieval
Give LLM-based agents precise, scoped context from the knowledge graph instead of raw document search or vector drift.
Change impact analysis
Trace the blast radius of a design change across requirements, test evidence, suppliers, and compliance artifacts in seconds.
Cross-domain traceability
Follow a requirement from its origin through design, test, and production — across tool boundaries — with full lineage.
Field intelligence feedback
Connect field returns and warranty data back to design and test nodes, closing the loop from production to engineering.
06Trust · enterprise grade
Built for regulated engineering.
DCH is designed from the ground up for engineering organizations that operate under strict data governance, compliance, and security requirements.
Deployment
On-prem · VPC · EU-sovereign cloud
Run DCH where your data governance requires — including fully air-gapped environments.
Governance
Role-based, attribute-based, program-level ACL
Fine-grained access control at the node and edge level, inherited from source systems.
Compliance
TISAX Level 2, GDPR, ISO 27001
Designed and audited for regulated engineering environments in automotive and aerospace.
Audit
Full lineage, versioned, tamper-evident
Every fact, every relationship, every change — fully traceable and immutable.
Data Context Hub
Unify your engineering context.
See how the Data Context Hub can turn your fragmented tool landscape into a governed, traversable knowledge graph.