LLM Evaluation Health Check
Find out where one RAG or agent workflow fails, why, and what to fix first.
- Price
- EUR 2,950 excl. VAT Fixed project fee
- Time
- About 5 working days
- Scope
- One RAG or agent workflow, up to 50 test cases
An independent view on whether a knowledge graph will improve your retrieval, before you commit engineering time.
At a glance
Contracted with and invoiced by MILEAWAY AI SYSTEMS LIMITED.
Teams considering a knowledge graph or GraphRAG for search, question answering or an agent, who want to know whether it is worth the effort for their data and their users' questions.
GraphRAG is often proposed as the fix for weak retrieval. Sometimes it is the right answer; sometimes better chunking, metadata or hybrid search would deliver more for less. The choice is hard to reverse once a team has built around it.
Limits. The recommendation is based on the samples, documentation and questions provided during the assessment. It is not a build or a performance guarantee. Implementation is scoped separately, for example as a Knowledge Graph Prototype Sprint.
Prices are in euro and exclude VAT, which is added where applicable. Any third-party costs, such as model or cloud usage, are confirmed in the quotation. Engagements are contracted with and invoiced by MILEAWAY AI SYSTEMS LIMITED.
Send me a short description of the use case and the data involved. I'll reply to arrange a discovery call.
A short call about the use case, the data and what decision you need to make.
A written scope and fixed-fee quotation covering the use case, the data samples, access and timing.
I review the questions and the data, and compare graph, vector and hybrid options for your case.
The architecture recommendation and roadmap, walked through with your team.
I've built AI systems in financial services and insurance, and I speak and write in public about evaluating LLMs and putting knowledge graphs to work. You can check all of it.
Speaker, NODES 2025
Building Contextual Knowledge Graphs to Adapt, Evaluate, and Leverage LLMs
Watch the session on YouTubeRecognition
Neo4j Featured Community Member, November 2025
Read the feature on neo4j.comWriting
Evaluating a Fine-Tuned LLM Using a Knowledge Graph and Ground Truth Data
Read the article on MediumExperience
Production AI, including financial services and insurance
Experience on LinkedInNo. If you already run Neo4j, I assess how your existing graph could support retrieval. If you don't, the assessment covers whether a graph is worth adding at all.
No. If better chunking, metadata or hybrid search would do more for less, the recommendation says so.
Your team can build from the roadmap, or I can scope a Knowledge Graph Prototype Sprint to test the recommended approach on your data.
Access, data handling and confidentiality terms are agreed in writing as part of the scope, before any work starts. I only ask for the access the agreed work needs.
Find out where one RAG or agent workflow fails, why, and what to fix first.
A working Neo4j and GraphRAG prototype on your own data, with evaluations built in.
Contact
Book a 30-minute call, or send a few lines about what you're building and what's going wrong.