Data consultancy from
engineers who'd actually
build what they recommend.
Most data consultancy work hands you a slide deck and an invoice. Ours comes from the same senior engineers who build data platforms day to day — a clear-eyed audit of your data strategy, stack and roadmap, with a documented set of recommendations in as little as 2 weeks.
The problems that bring
teams to us for an outside opinion.
If any of these sound familiar, the fix usually isn't another internal workshop — it's a genuinely independent read. Here's how we approach it.
No independent read on the data strategy
Everyone inside the building already has a stake in the current answer being the right one.
Not sure if it's the tools, the team, or the process
Is it the platform, the process, or the people — nobody's stepped back far enough to actually tell.
A vendor recommending their own roadmap
Every audit from a platform vendor conveniently discovers you need more of what they happen to sell.
Big data bets made on gut feel
Platform migrations and tooling decisions get made in a meeting, then lived with for years.
A strategy that gets used,
not just approved.
Most data consultancy work stops at a slide deck. Ours is a working decision framework — built with your actual constraints, tied to business outcomes, and handed to a team that could execute it tomorrow if you asked.
A data strategy is a decision framework, not a slide deck.
Most data consultancy work is a slide deck for a board meeting, filed away and never opened again. Ours is a working decision framework — one your team can use to make the next platform bet, the next governance call, the next hire, without commissioning a new report each time.
Grounded in your constraints, not a template
Every recommendation is tested against your actual data, team and budget — not a generic maturity model copied from the last client.
Tied to business outcomes
We map every data decision back to the metric it's meant to move — cost, speed, risk or revenue — so priorities are obvious, not political.
Written for the board and the backlog
One document, two audiences: a framework leadership can approve, translated into decisions your data team can action next sprint.
The people who advise are the people who'd build
Our recommendations come from engineers who build data platforms in production, not consultants handing you a plan someone else has to make real.
A working method, not a deck of phases.
Discover
We get into the detail. Stakeholders, constraints, data, and the real problem you're trying to solve.
Strategise
We sketch the smallest version that proves the outcome. A clear plan, a tight scope, no fluff.
Build
Cross-functional pods of engineers, designers, and data folk. Working software every week.
Scale
We harden it, instrument it, and stick around. Roadmaps, reviews, and a team that knows your stack.
Not sure if you need a strategy or just a second opinion? Ask the engineer who'd make the call.
Book a 30-minute working session with a senior data engineer — a real conversation about your data, not a sales call.
Built with clients
who measure outcomes.
A 12-tab spreadsheet, rebuilt as a risk platform
Offshore cable burial risk assessment taken out of a straining Excel workbook and rebuilt as a Python engine and React application on Microsoft Azure — a hundred thousand rows of AIS vessel data, Carbon Trust anchor-strike methodology, and depth-of-lowering curves for every soil zone on a route.
Frasers Aerospace — Operations Control Tower
An operations dashboard for an AS9120B aerospace supplier, built in Microsoft Lists and Power BI — orders from Sage 200 and WooCommerce in one place, the spreadsheets they used to be raised in retired, the exceptions blocking them surfaced first, and a TV wallboard for the warehouse floor.
“The best data audits don't end with a slide that says 'hire more data engineers.' They end with a short list of decisions someone can actually make on Monday morning.”
Sectors we've advised on data for.
We've shaped data strategy and roadmaps for teams across all of these sectors.
What we plan with.
Pragmatic, mostly boring, and chosen because they get a real answer fast — not because they're on the front page of Hacker News.
Architecture & planning
- Miro
- C4 Model
- Notion
Data & analytics platforms
- Snowflake
- Power BI
- Databricks
Due diligence & audit
- SonarQube
- Snyk
They were very responsive regarding requests during and after the project was completed.Read more client stories
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Data consultancy services,
and where they lead.
Data engineering
We design and build the data infrastructure that powers intelligent decision-making — from ingestion to insight.
Learn moreData products
Standalone data products your team can actually use.
Learn more 02Data solutions
Bespoke solutions to your most complex data challenges.
Learn more 03BI & analytics
Dashboards and reporting tools that turn raw data into clear decisions.
Learn more 04Machine learning & MLOps
Predictive models and ML pipelines designed for production.
Learn more 05Data consultancy
Strategic advice on how to structure, govern, and get more value from your data.
Learn moreQuestions, answered straight.
Have an outcome in mind?
We'll help you
ship it.
- You're building a data product and need a team that can deliver.
- You want to get AI-ready — pragmatically, not theoretically.
- Your reporting is a mess and you need a real platform underneath it.