01
Reliable reporting
Reconcile records, agree definitions and build views that explain performance across teams and systems.
Data & AnalyticsUnderstand the business.
Understand the business.
See the next move.
We build the data foundations, reporting and predictive models behind better business decisions. From customer economics to capacity and demand, the work starts with the decision you need to make.
Data foundations · forecasting · decision models
Related workDistil.ai2 to 4 weeksto a focused working proof
Senior engineeringresponsible for the implementation
Magus.DATA & ANALYTICS
From business data to decisions
ExampleHistorical demandForecast range
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ConnectAgreed records and definitions
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UnderstandPatterns, performance and exceptions
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PlanTested forecasts and decision signals
Data the business can use and check.
Connect the records and agree the definitions.
01 · THE WORK
Built around the way your business works
We build the data foundations, reporting and predictive models behind better business decisions. From customer economics to capacity and demand, the work starts with the decision you need to make.
02 · THE IMPLEMENTATION
Where we put it to work
02
Customer intelligence
Understand acquisition, repeat purchase, retention and the differences between customer groups.
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Planning and prediction
Forecast demand, prioritise opportunities and surface operational exceptions where the available data supports a useful model.
03 · THE IMPLEMENTATION
What the implementation includes
01
Connected data
Identify the source of each measure, resolve mismatched records and make freshness and quality visible.
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Decision focused tools
Build dashboards, models and explanations around an owner and a concrete action.
03
Measured performance
Compare models with a baseline and monitor accuracy, data changes and business usefulness after release.
IMPLEMENTATION EXAMPLE
Revenue and acquisition reporting that reconciles to finance
The reporting period closes, but ad platform, order and finance totals disagree.
THE EVIDENCE
What the system needs
- Order and subscription events
- Ad spend, channel and customer identifiers
- Refunds, cancellations, settlements and finance totals
THE CHECKS
What this example checks
- Resolve customer and order identifiers across systems.
- Apply finance approved treatment of cancellations, refunds and recognition events.
- Reconcile the closed period before switching the team to automated reporting.
THE WORKING RESULT
What reaches the team
A tested reporting model connecting acquisition spend to real orders and the financial records behind them.
The decision boundaryFinance owns recognition rules and signs off reconciliation differences; the model does not invent accounting treatment.
WHAT THIS EXAMPLE WOULD TEST
Use a closed period with approved totals. Check unmatched orders, duplicate events, unexplained reconciliation differences and time needed to produce the report.
Illustrative implementation scope. This describes a possible build, rather than a claimed client result.
05 · THE WORK
A practical first project
Choose one commercial or operational decision. We check the available history, build a reliable baseline and test whether better data or a model changes that decision.
A focused proof of concept ships in 2 to 4 weeks. Production scope follows the evidence, including integrations, testing, rollout and support.
SOLUTIONS WE BUILD
From the service to the system.
RAG & Knowledge Systems
Company knowledge systems with relevant sources, current versions and appropriate access.
Data, Predictive Models & BI
Data foundations, predictive models and BI built around commercial and operational decisions.
Dashboards, Integrations & Workflow Systems
Connected systems for operational visibility, reliable integrations and clear ownership of work.
YOUR NEXT STEP
Which decision needs a clearer view of your business?
Bring us one workflow, real examples and the people who know the work. We’ll identify a practical first build.