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Knowledge Graph & GraphRAG Development Services

Turn scattered documents, records and systems into a connected knowledge graph, so your AI can follow relationships and answer complex questions with sources.

Explore LLM & RAG

At a glance

Graph data modelling and ontology design
Entity and relationship extraction from documents
GraphRAG pipelines with source citations
Integration with Dynamics 365, SharePoint and databases
Role-based access and evaluation built in

A knowledge graph stores your business data as connected entities and relationships, such as customers, contracts, products and people, so AI can follow the links between them. GraphRAG combines that graph with retrieval-augmented generation, letting an LLM answer multi-step questions with sources instead of guessing.

What we deliver

Knowledge graph services, end to end

From modelling your domain to a production GraphRAG assistant your teams can trust.

Graph modelling & ontology

Define the entities, relationships and rules that describe your business, aligned to how your teams ask questions.

Knowledge extraction

Extract entities and relationships from contracts, manuals, tickets and emails into a structured graph.

Graph database implementation

Set up and tune graph storage on platforms such as Neo4j and Azure options, sized for your data and security needs.

GraphRAG pipelines

Combine graph traversal with vector search so answers use both meaning and relationships, with citations.

Enterprise data integration

Connect Dynamics 365, SharePoint, ERP and databases so the graph stays current.

Governance & evaluation

Access control, audit trails and answer-quality testing so the system stays trustworthy as it grows.

Use cases

Where knowledge graphs pay off

Customer 360See how accounts, contacts, orders and cases connect across systems.

Contracts & complianceLink clauses, obligations, suppliers and regulations for faster review.

Supply chain tracingTrace parts, suppliers and dependencies when something changes.

Enterprise searchAnswer questions that need several documents and systems at once.

Technology

Built on proven platforms

Neo4jAzure Cosmos DBAzure AI SearchAzure OpenAIMicrosoft FabricPythonLangChainLlamaIndexDynamics 365SharePoint

How we work

From data to connected intelligence in five steps

1Discover

Use cases, questions and data sources.

2Model

Ontology and graph schema design.

3Build

Extraction, graph load and retrieval.

4Evaluate

Test answers for accuracy and access.

5Launch

Deploy, monitor and improve.

Security you can verify

ISO/IEC 27001:2022 certified

Graph projects often involve sensitive contracts and customer data. We handle them under our certified Information Security Management System, with role-based access carried through to every answer.

Quick answers

Frequently asked questions

What is the difference between RAG and GraphRAG?

Standard RAG finds text passages similar to a question. GraphRAG also uses a graph of entities and relationships, so it can connect facts across many documents and answer questions that need several steps.

When do I need a knowledge graph?

A graph helps most when answers depend on relationships between things, such as suppliers, contracts and products, or when questions span several documents and systems.

Can you connect it to Dynamics 365?

Yes. We integrate Dynamics 365, SharePoint and your databases so the graph and the answers stay up to date, with permissions respected.

Do you only use Neo4j?

No. We choose the graph platform that fits your data, security and cloud, including Neo4j and Azure-based options.

LLM & RAG Services Agentic AI & Copilot Studio AI Readiness Assessment Azure AI Services

Ready to connect your knowledge?

Book a free discovery call and we will map your data, questions and first graph use case.

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