pre-mvp

Data & knowledge

Build the semantic layer your legacy estate cannot provide by itself.

Legra gives data leaders, architects, modellers, engineers, stewards, and governance teams a shared destination for meaning. Existing databases, files, APIs, messages, documents, media, and pipelines can be connected progressively while the Enterprise Knowledge Graph captures the concepts, relationships, provenance, contracts, and ownership that source systems do not express.

What changes

Connect legacy data without pretending every source already shares one model or identifier scheme.

Create a semantic layer that people, applications, analytics, and agents can use together.

Treat workspaces as independently governed Data Products with ownership, history, contracts, and access policy.

Branch, validate, review, and merge graph changes before they alter trusted shared knowledge.

Preserve provenance from source ingestion through transformation, inference, human review, and operational use.

Grow toward an Enterprise Knowledge Graph one domain and Use Case at a time.

Legacy integration with shared meaning

ETL remains useful, but moving columns is not enough. Legra adds explicit semantics, identity, provenance, and graph relationships so data from incompatible systems can participate in the same business context.

Data Products meet real demand

Data Products form the supply side of the data economy; Use Cases form the demand side. Contracts and ports describe how governed knowledge can be discovered, acquired, combined, and invoked rather than merely copied into another lake.

The graph is an operating corpus

Models, ontologies, taxonomies, rules, documents, media, conversations, task evidence, and derived facts belong around the business objects they describe. That makes the graph useful for operational work and AI, not only data discovery.

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