— Partnership / 03
Databricks · Data & AI Partner

Built on Databricks.
Governed before you scale.

We are an engineering-led partner. Our engineers build the data foundation against your problem before you scale on it — a governed lakehouse in weeks, a migration your team can trust, and analytics and AI that run on one source of truth. The proof is a platform you can build on.

Posture / Demo-first Platform / Lakehouse · Unity Catalog · Mosaic AI
§ 01
How a Databricks engagement runs
I.
Prove.
Your first meeting includes a working slice — a governed table and a live pipeline built on Databricks against your actual data, not a slide about it. You watch your own numbers move, and the conversation changes shape.
Meeting one
II.
Land.
The lakehouse foundation, compressed. Delta and Unity Catalog stand up the governed core, and we migrate the warehouse or lake that is slowing you down — in weeks, with lineage and access control from day one.
Weeks, not quarters
III.
Compound.
The platform becomes an operating capability. Analytics, ML, and applied AI all run on one source of truth, and Platform Operations runs it 24×7 — DataOps and MLOps — while your own team learns to lead the next build.
Quarter on quarter
§ 02
The platform · what we build on
— Pillar / 01 · The foundation

Lakehouse.

One source of truth.

Delta at the core — batch and streaming on open formats, no copy sprawl. We migrate legacy warehouses and lakes onto a medallion architecture, so every team reads from the same governed tables instead of arguing about which extract is right.

BuildDelta · medallion · streaming + batch
FromWarehouses · lakes · legacy ETL
ForTeams tired of copies that disagree
— Pillar / 02 · Governance

Unity Catalog.

Govern once, everywhere.

One permission model across data and AI — tables, files, models, and dashboards. Column-level control, end-to-end lineage, and secure sharing through Delta Sharing. Governance is designed in from the first table, not bolted on before an audit.

BuildAccess · lineage · audit · Delta Sharing
CoversData · ML models · dashboards
ForRegulated data that must stay traceable
— Pillar / 03 · Applied AI

Mosaic AI.

From data to production AI.

The path from governed data to shipped intelligence — MLflow for the lifecycle, model serving, vector search, and RAG and agents grounded in your own tables. AI that inherits the governance and lineage of the data underneath it.

BuildMLflow · serving · vector search · RAG
Runs onYour governed lakehouse
ForAnalytics teams shipping real AI
§ 03
Blueprints · opinionated, end to end

The patterns
we keep shipping.

We build data foundations and the AI on top of them for banks, insurers, manufacturers, and retailers. Two shapes recur — whatever the estate.

Anonymised accounts of comparable work are on the Work page. Both blueprints draw end to end — at 1× speed, the way we sketch them in the first working session.

— Blueprint 01 / The governed lakehouse

One platform,
every team.

For any business running on copies that disagree. Sources land once through Delta Live Tables and Auto Loader, batch and streaming together, into a medallion lakehouse on Delta.

Unity Catalog governs all of it — one permission model, column-level control, lineage from source to dashboard. BI, SQL, and Mosaic AI read from the same governed truth. Run 24×7 by Platform Operations.

03 Data → 02 Cloud → 01 AI → 05 Operations · governed by Unity Catalog
Databricks Sources databases · apps · files · events Ingestion Delta Live Tables · Auto Loader batch + streaming, once Lakehouse Delta · medallion one source of truth BI & SQL dashboards · queries AI & ML Mosaic AI · MLflow Apps & APIs serving · reverse ETL — governed by Unity Catalog · lineage · access control · DataOps 24×7
— Land once, read everywhere · every layer governed
— Blueprint 02 / Data to decisions

Operations that
see ahead.

For manufacturers, retailers, and lenders — any business that moves things or prices risk. The operational exhaust of ERP, CRM, POS, and telemetry streams into the lakehouse, fresh instead of nightly.

The lakehouse feeds two consumers — pipelines that forecast and optimise demand, risk, and maintenance, and Mosaic AI copilots that put the answer where the work happens. Governed by Unity Catalog, run by Platform Operations.

03 Data → 01 AI → 05 Operations · DataOps · MLOps
Databricks Operational exhaust ERP · CRM · POS · telemetry Streaming ingestion Auto Loader · Delta Live Tables — fresh, not nightly Lakehouse Delta · Unity Catalog · one semantic layer Forecast & optimise ML pipelines · MLflow demand · risk · maintenance AI copilots Mosaic AI · agents answers where work happens — run 24×7 · DataOps · MLOps · governed by Unity Catalog
— Exhaust to stream, stream to decisions · drawn at 1× speed
§ 04
What we build on Databricks · by capability
— Data platform
  • Delta lakehouse — medallion
  • DLT · Auto Loader — ingestion
  • Streaming + batch
  • Warehouse & lake migration
— Governance
  • Unity Catalog — one model
  • Lineage — source to dashboard
  • Delta Sharing
  • Access control · audit
— AI & ML
  • Mosaic AI — RAG · agents
  • MLflow — lifecycle · serving
  • Vector search
  • Feature engineering
— Operations
  • 24×7 run — DataOps · MLOps
  • Cost & performance — tuned
  • Data quality · tests
  • Reliability · SLAs
§ 05
Evidence · stated plainly

What we can show today.

We joined the Databricks partner network in 2026, and we publish evidence the way we build — without inflation. Named lakehouse case studies will land here as the first engagements close. Until then, the demo is the reference — a governed slice on your own data, in the first meeting.

Request the demo
Working demos A governed table and a live pipeline on your own data — ask for the slice nearest to your estate
Platform Lakehouse, Unity Catalog, and Mosaic AI — the Databricks stack, built into production
Prior work All three pillars, delivered in prior work — through cloud and data consultancies the founding team built and ran through to acquisition, with comparable engagements anonymised on the Work page
Named case studies Expected as first engagements close — later in 2026
Bring us the data you
cannot trust yet — we will bring it governed.

Working sessions, not sales calls — a governed slice on your own data, in the first meeting.

Begin a conversation