Service · KNOWLEDGE + DATA
AI answers grounded in your truth.
Knowledge & Data Engineering. RAG, knowledge graphs and structured catalog data that make every answer traceable to a source you own.
Who this is for
Built for teams like yours.
- Teams whose assistants hallucinate policy, pricing or product facts
- Catalog-heavy businesses that need AI-consumable data
- Organisations with knowledge locked in documents and wikis
What the FDE team does
Inside your stack, not around it.
- RAG pipelines with measured retrieval quality
- Knowledge graphs and vector search
- Data contracts between source systems and agents
- Structured product and catalog data for AI consumption
- llms.txt and schema markup
The outcomes you get
Scored, not promised.
[X]%
Answers with verifiable citations
Illustrative · placeholder
−[X]%
Hallucination rate
Illustrative · placeholder
[X]x
Faster knowledge onboarding
Illustrative · placeholder
Frameworks & tools we bring
Model-agnostic by design.
pgvectorVertex AI SearchBedrock Knowledge BasesNeo4jdbtSchema.org
Related case study
Raising AI accuracy for an enterprise running AI in production
ReadPut an FDE pod on knowledge & data engineering.
Start with an outcome audit. We’ll map the systems, measures and FDE pod needed to move from AI ambition to production impact.