GraphRAG Implementation Services for Your Business
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.
How graphrag implementation works, step by step
A made-up example of one run, from start to finish. Each step is logged so you can see what happened.
- Your documents are loaded
Files are split, indexed and kept in your own storage.
- A question comes in
The system finds the parts of your documents that match.
- The model answers from them
Answers point back to the source so people can check.
- People review the edge cases
We agree what happens when no good answer is found.
Sample Made-up names, data and steps to show how a run is logged. Your steps, tools and rules follow your business.
What you get with graphrag implementation
Advanced Graph Retrieval-Augmented Generation linking entities, concepts, and dependencies into Neo4j knowledge graphs. Resolving complex multi-hop enterprise reasoning queries.
Basic Package
Entity extraction from up to 200 docs into Neo4j, graph Q&A. 7-day delivery, 1 round + 30-day fixes.
Standard Package
Up to 2,000 docs, custom schema, multi-hop GraphRAG queries, docs. 12-day delivery, 1 round + 30-day fixes.
Premium Package
Up to 10,000 docs, hybrid graph; vector, incremental updates, 30 days support. 20-day delivery, 1 round + 60-day fixes.
Clear brief first
We confirm what you need before work starts, so the scope is clear on both sides.
Revisions listed
Each package shows its revision rounds. A round is one list of changes sent together.
Yours once paid
Copyright of the final work passes to you once the order is paid in full.
Third-party tools, API usage and hosting are billed to your own accounts, so the setup stays with your business.
How our graphrag implementation works
Pick the questions
We list the multi-step questions the system must answer.
Design the schema
Entities and relationships are defined from your documents.
Extract and load
Documents are processed into Neo4j and checked.
Query and test
GraphRAG queries are tested against your questions.
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.
In short
- Delivery in 7 to 20 days, by package.
- Fixed price, shown before you order.
- Teams whose RAG answers fail on questions that join facts from several documents.
- Compliance and legal staff tracing dependencies between policies and contracts.
- Copyright yours after full payment.
Graphrag Implementation: common questions
How much does graphrag implementation cost?
Prices are fixed and shown by package on our Graphrag Implementation pricing page, so you see the full price before you order. You can also ask for a custom quote.
How long does Neo4j knowledge graph consulting take?
Delivery depends on the package: Basic 7-day delivery; Standard 12-day delivery; Premium 20-day delivery.
What is included in the Basic Package?
The Basic Package includes: Entity extraction from up to 200 docs into Neo4j, graph Q&A. Higher packages add more scope, revisions and support.
Can I get a custom graph RAG development package?
Yes. If none of the packages fits, use the custom package form on our pricing page to describe what you need, and our team sends you a fixed price.
Do I need GraphRAG or ordinary RAG?
If your questions need facts joined across documents, GraphRAG helps. For simple lookups, ordinary RAG is often enough.
Do I need Neo4j already?
No. We set up the graph.
Can the graph update as documents change?
Premium adds incremental updates.
Can graph and vector search work together?
Yes, Premium offers a hybrid approach.
What is a knowledge graph for an LLM?
It is a database of entities and the relationships between them, which a language model queries to answer questions that depend on connected facts. It complements text search rather than replacing it.
Who owns the final work?
Copyright of the final work passes to you once the order is paid in full. Paid fonts, stock files or licences, if used, are licensed in your name.
Ready to start your graphrag implementation?
Compare the packages and pick the one that fits. Not sure which? Write to us and we will help you choose.