01
Data Strategy & Maturity
Operating model, data roadmap, maturity assessment, business case — aligning data investment with P&L outcomes.
Maturity assessmentRoadmapsOperating model
#strategy
Know where you are, plan where to go.
A data strategy that survives first contact with delivery. We sequence the moves, tie investment to P&L, and make the plan something your team can actually ship.
Maturity model
Where most teams sit — and where they’re trying to get.
- 01ReactiveSpreadsheets. Tribal knowledge.
- 02RepeatableA warehouse exists. Reports ship.
- 03DefinedGovernance and lineage are real.
- 04ManagedQuality and SLAs, not vibes.
- 05OptimisingData is a product, measured in P&L.
#foundations · data domain
The plumbing that makes the answer trustworthy.
Pipelines, platforms, governance, analytics. The layer dashboards and models depend on — so what comes out isn’t lying to you.
02
Data Engineering & Platforms
Pipelines, warehousing, lakehouse, cloud modernisation — the plumbing and foundation.
FabricSynapseDatabricksSnowflakeData LakeAWSGCP
03
Data Governance & Quality
Catalogues, lineage, MDM, profiling, observability — so dashboards and models aren't lying to you.
PurviewData FactoryLineageMDM
04
Data Analytics & BI
Dashboards, self-serve, custom visuals, analytical workflow apps — the answer at a glance.
Power BITableauLookerPower AppsPower Automate
#delivery · how we work
The same people, from the whiteboard to production.
Four principles that decide how we staff, scope, and ship. They’re also why we turn work down when the shape’s wrong.
One team, end to end
The same people shape the strategy and ship the pipelines. Nothing gets rebadged at a handoff.
Outcome-owned
We sign up to the metric that matters — adoption, cycle time, margin — not just the deliverable.
Senior on the keyboard
No pyramid. The consultant who scoped the work is the one still there at go-live.
Productionised, not prototyped
Pilots only count when they survive ops, audit, and the next budget cycle. That's the bar.
#intelligence
AI, made real.
Beyond demos. Predictive models, copilots trained on your data, and early agentic prototypes — grounded in what your business already knows, safe by design.
05
AI & Generative AI
Predictive models, NLP, computer vision, RAG, copilots, enterprise chat — trained on your data.
Purview MLBigQuery MLOpenAIAzure OpenAIRAG
06
Agentic AI
EmergingEarly experiments and prototypes. Not yet a core production offering — surfaces on enquiry when a project is a good fit.
#candour
What we don’t do.
Saying no is a capability. Three lines we won’t cross, so the ones we do cross mean something.
- We don't sell licences we can't implement.
- We don't run change programs without a data foundation underneath.
- We don't dress pilots up as production.
#tools · the stack
A focused toolkit, not a sprawling menu.
Sixteen named tools across three groups. The real stack we deliver on — if we don’t list it, we don’t claim it.
Microsoft ecosystemPrimary
Microsoft FabricSynapsePower BIPower AppsData FactorySQLPurview MLPower Automate
Data & Cloud platforms
DatabricksSnowflakeData LakeAWSGCPBigQuery
Visualisation & BI
Power BITableauLooker
#partners · the ecosystem
Tiered alliances, not a badge collection.
Each partnership here maps to real project history — co-delivered work, certified people, joint customers. We earn these; we don’t collect them.
MicrosoftSolutions Partner — Data & AI
SnowflakeSelect Services Partner
KPMGDelivery Alliance
OpenAIAPI Platform
#common questions
What most teams ask before they engage.
Five questions that come up on almost every first call. Short, honest answers.
How does an engagement start?
A 30-minute discovery call with a senior consultant — no pitch deck. We pressure-test where you are, where the value is, and whether we're the right team. If it's not a fit, we'll say so and point you somewhere that is.
Do you work fixed-price or time-and-materials?
Both. Strategy and discovery work is typically fixed-price against a defined scope. Build and run work is usually T&M against a capped envelope, with go/no-go decision points every few sprints so budget stays honest.
What size of business is this for?
Mid-market through enterprise is where we spend most of our time — organisations with enough data to matter and enough complexity that generic tooling has stopped working. We also take on smaller engagements when the problem is sharp and the buyer is clear.
Can you work alongside our incumbent vendor?
Yes, and we often do. We're platform-fluent rather than platform-dogmatic. If you already have a Databricks contract or a Power BI estate, we build on it — we don't rip and replace for the sake of it.
How fast can we see value?
A maturity assessment delivers a usable roadmap inside six weeks. A focused foundations build — one pipeline, one dashboard, one governed dataset — typically shows value in 8–12 weeks. AI work varies more; we'll be upfront about what's realistic before you spend anything.
Where are you on the maturity curve?
Thirty minutes with a senior consultant. We’ll pressure-test where you are, where the value is, and whether we’re the right team to help you get there.