The data foundation your AI actually needs.
An orchestra cannot play from scattered sheet music. We build the pipelines, models and platforms that make your data reliable, connected and ready for AI — governed once, reused by every use case.
The problems this solves.
Every AI project starts from zero
Each team rebuilds the same extracts and copies the same data into a new silo, so nothing compounds and nothing is governed.
The model is fine; the data isn't
Retrieval returns stale or duplicated content, entities don't line up across systems, and the answer quality has nowhere to go.
Nobody trusts the numbers
Reports disagree, lineage is unknown and access is either wide open or impossible to get.
Capabilities, in the order they're usually needed.
Not a menu to pick from — a sequence. Most engagements start at the top and stop when the business number moves.
Data pipelines
Batch and streaming pipelines with tests, lineage and alerting, built on your cloud's native tooling or open-source engines — whichever your team can run.
Data architecture
Lakehouse, warehouse and operational stores shaped around how the data is used, including the access patterns AI retrieval needs.
Data integration
Connectors and change-data-capture from your ERP, CRM, ticketing and line-of-business systems, with entity resolution across them.
Knowledge graphs
Graph models that connect customers, products, documents and events, so agents can reason over relationships instead of guessing from text.
Vector databases and retrieval
Embedding pipelines, hybrid search, re-ranking and freshness handling tuned on your content, with evaluation to prove it.
Data governance
Catalogue, ownership, quality rules, retention and access control designed for GDPR and sector rules, enforced in the platform rather than in a policy document.
AI-ready enterprise data
Curated, documented datasets and feature stores that any use case can draw on — the asset that makes the second AI project faster than the first.
How this fits the orchestration.
Data is the section of the orchestra that every other section depends on. In our orchestration model it is governed once and reused everywhere, which is what turns a pile of pilots into a platform.
Orchestration is the layer between your business goals and your AI capabilities — the part that decides what to build, how it fits together and how you know it's working. See how orchestration works.
Deliverables you can use.
Every engagement ends with something that works without us: documents your board can read, systems your engineers can run.
- Data architecture and roadmapTarget design, platform choices and the sequence to get there without stopping the business.
- Production pipelinesTested, monitored pipelines with lineage, running on your infrastructure.
- Knowledge graph or retrieval layerModelled, loaded and evaluated against the questions your use cases ask.
- Governance frameworkCatalogue, ownership, quality and access rules — implemented, not just written.
- Documentation and hand-overRunbooks, data contracts and training so your team owns the platform.
Usually played together.
Ready to bring your AI into tune?
Tell us the business goal. In a 30-minute call we'll show you how we'd score it — which instruments, in which order, measured how.