Graphwise

Graphwise is the company behind GraphDB, an established RDF graph database designed for standards-based knowledge graph, semantic data, and Al-ready enterprise architectures.

Datavid partners with Graphwise to help organizations move from fragmented data, documents, and domain knowledge to connected, governed, and queryable knowledge layers.

Datavid brings deep expertise in semantic data, ontology modeling, data engineering, and GraphRAG. Combined with Graphwise's graph technology, this helps clients turn complex information into reusable, Al-ready knowledge.

About Graphwise

Graphwise, formed by the merger of Ontotext and Semantic Web Company, is known for GraphDB, one of the established RDF graph databases in the semantic technology market.

GraphDB is designed for organizations that need open, interoperable, and standards-based graph data. It helps teams build knowledge graph solutions that avoid proprietary lock-in and support long-term data reuse.

Graphwise technology is especially relevant where organizations need to:

• Model domain knowledge using shared semantics
• Connect structured and unstructured data
• Use ontologies and taxonomies to add context
• Support reasoning and inference over enterprise knowledge
• Prepare data for GraphRAG and Al applications
• Improve explainability, traceability, and governance in Al workflows

This makes Graphwise a strong fit for regulated, knowledge-intensive industries where data needs to be connected, trusted, and reusable.

Datavid and Graphwise

Datavid's work with Graphwise builds on years of experience delivering semantic data, knowledge graph, and Al-ready data solutions for enterprise clients.

Datavid brings the implementation layer: the data engineering, ontology modelling, integration, enrichment, governance, and application development needed to turn graph technology into production ready business solutions.

Our role is to help clients understand where knowledge graphs and semantic technologies can create value, design the right architecture, and deliver the end. to-end solution around the platform.

This includes:

• Data integration across source systems
• Semantic modelling and ontology alignment
• Entity extraction and enrichment
• Knowledge graph design and implementation
• GraphRAG and Al-ready data foundations
• Semantic search and discovery applications
• APls, user interfaces, and workflow integration
• Governance, lineage, and access-control considerations

The partnership supports a practical, client-led approach. Datavid remains platform-aware and technology-agnostic, recommending architecture choices based on each client's requirements, existing environment, and target use case.

Why this partnership matters

From fragmented data to connected knowledge

Many organizations have valuable data, but it is often fragmented across documents, repositories, applications, research systems, and operational platforms.

Graphwise provides the graph technology foundation for connecting this information through shared meaning.

Datavid helps design, build, and operationalize the full solution, from source integration and semantic enrichment to knowledge graph delivery, GraphRAG, and user-facing applications.

Standards-based semantic architecture

Graphwise's support for RDF, OWL, and SPARQL gives organizations an open, standards-based foundation for knowledge graph development.

This is valuable for enterprise teams that need interoperability, long-term flexibility, and reduced risk of proprietary lock-in.

Better context for Al

Al systems are only as useful as the data and context they can reason over.

By combining Graphwise's graph technology with Datavid's semantic data and GraphRAG expertise, organizations can ground Al outputs in connected knowledge, supporting better traceability, explainability, and trust.

Faster path from use case to production 

Datavid helps clients move from concept to implementation by combining strategic scoping, technical delivery, reusable accelerators, and domain experience.

This helps reduce the gap between graph technology potential and business-ready outcomes.

Relevant use cases

• Scientific knowledge management
• GraphRAG and trusted Al
• Ontology-driven knowledge graphs
• Semantic search and discovery
• AI-ready foundations

Related resource:

Watch the Datavid and Graphwise webinar: The Missing Layer Between Scientific Data and Breakthrough Ideas