From messy data to decisions you can trust.
Every example follows the same shape: the problem a business was stuck on, what we built, and what changed. These are illustrative examples of our work. Real, named client stories are published here as they’re approved.
A closer look at one transformation
The full story, the problem, the pipeline we built, and what changed for the team.
Automated Multi-Client Marketing Reporting
How a marketing agency's monthly reporting grind became an automated, on-brand reporting engine, with AI drafting the commentary and account managers approving it.
- ConnectPull each client's ad, social, analytics and CRM data automatically.
- StandardizeMap every platform to one consistent, comparable KPI model.
- DraftAI writes the per-client commentary and action plan for review.
- DeliverOn-brand reports sent on schedule to every client.
- From days to automaticMonthly report building went from a manual scramble to a process that runs itself.
- One consistent standardEvery client sees the same trustworthy KPIs, on-brand, every time.
- Scales with each new clientAdding a client no longer means adding hours of reporting overhead.
- Commentary written for reviewAI drafts each client narrative from the numbers. A person edits and approves before sending.
The complete systems, use case by use case
Reporting & BI, measurement & attribution, data platforms, AI & automation, sales and finance. Open any one for the problem, the build and what changed.
Migrating Off Legacy BI Without Losing a Number
Result The business moved onto a modern, maintainable, self-hosted reporting stack with its numbers intact and its metric logic finally documented, and the legacy licences were actually cancelled.
Read the exampleA Consistent Scorecard Across Every Location
Result Leadership got one consistent, current view of every location, underperformance surfaces itself early, and nobody rebuilds the network roll-up by hand.
Read the exampleMarketing Attribution From First Click to Revenue
Result Every customer now traces back to the channel, campaign and content that created them, and budget and content decisions are made on revenue rather than last-click guesses.
Read the exampleReliable Conversion Tracking Across Complex Journeys
Result Conversions are counted once, orders that pixels can never see are captured server-side, and the platforms, analytics and order database finally agree, so spend is optimised on data the team believes.
Read the exampleA Profitability Platform Across Stores and Marketplaces
Result Leadership sees net sales, total selling cost, profit and margin by marketplace, country and SKU in one place, week over week, and decisions about products, pricing and ad spend are made on contribution rather than top-line revenue.
Read the exampleOne Warehouse, One Set of Numbers
Result One governed set of numbers now serves every report, meetings argue about decisions instead of figures, and the AI on top answers from modelled, tested data rather than guesswork.
Read the exampleAn AI Operations Agent Running the Admin Layer
Result Requests stopped sitting unread, proposals go out the day they are asked for, invoicing follows completion without being remembered, and the team's time moved from administration to engineering.
Read the exampleDocument Intelligence for a Professional Practice
Result Documents file themselves and figures stop being retyped, clients are chased politely and automatically, and the firm's accumulated knowledge answers questions instead of sitting in folders, with a person approving everything that leaves the building.
Read the exampleScheduled AI Reports the Team Actually Reads
Result The Monday update writes itself and holds up to scrutiny, ad-hoc questions get answered from live data instead of interrupting an analyst, and a person still reviews anything before it leaves the team.
Read the exampleAI Lead Generation & Follow-Up That Never Goes Cold
Result Outreach runs on schedule with personalization that used to take an hour per prospect, replies are triaged instead of buried, and inbound leads get followed up while they are still warm.
Read the examplePayroll & Accounting Automation With Human Approval
Result Payroll preparation became a review task instead of a data-entry marathon, every entry is verified against what the API actually recorded, and the administrator retains sole control of submission.
Read the exampleHave a problem like these?
Talk to an ExpertThe same honest shape, every time
We do not lead with vanity metrics. Every engagement is framed around a real problem and a change you can see, which is exactly how these examples are written.
1 · The problem
We start with the decision you are stuck on and the money on the line, not the software.
2 · What we build
Connected data, reliable tracking, clear dashboards, automation and custom AI agents, built with Claude Code and fitted to your business.
3 · What changes
A concrete before-and-after: faster decisions, trusted numbers, hours saved, results you can point to.