Graphrag Implementation Services
Packages & Pricing.

GraphRAG implementation services with Neo4j knowledge graphs

GraphRAG implementation services connect your documents as a graph of entities and relationships, so an assistant can answer questions that need several steps of reasoning. Omeiro extracts entities from your files, stores them in Neo4j and builds queries that follow the links.

Ordinary vector search finds similar text. A graph can answer who reported to whom, which contract depends on which clause or what a policy change affects.

GraphRAG implementation: designing the schema before the extraction

The schema decides what the graph can answer. GraphRAG implementation begins with the questions: if users ask which supplier contracts reference a given regulation, the graph needs supplier, contract and regulation entities and the links between them. Collect ten to twenty real multi-step questions before ordering. Those questions determine which entity types and relationships are worth extracting, and they later serve as the test set for the finished system.

Extraction is imperfect, so build in checks. Models can split one entity into two spellings or invent a relationship, which is why entity resolution and sampling reviews matter. A practical GraphRAG implementation compares a sample of extracted facts with the source text and fixes the prompts before processing the full set. Think about updates too: documents change, and the graph must follow. Tell us your document types and volume so extraction time and effort are scoped properly.