Data science and AI analytics that answer real questions.
Dashboards and analysis that answer the questions your team actually asks, plus forecasting and AI-assisted analysis when the data can support it, always with a person reviewing what it finds.
What we build
From the first reliable dashboard to forecasting and AI-assisted analysis.
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Dashboards and self-service reporting
Power BI models and dashboards that your teams can filter, drill into and trust, refreshed automatically.
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Operational reporting
Daily and weekly views of operations, service levels and workloads, delivered where people already look.
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Financial and customer reporting
Revenue, costs, retention and customer behaviour, reconciled with your source systems.
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Forecasting and trend analysis
Forecasts for demand, cash flow, capacity and workload, with the uncertainty shown plainly.
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Segmentation and insight
Grouping customers, products or cases by how they behave, so effort goes where it counts.
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AI-assisted analysis
Language models that summarize feedback, documents and survey responses, with a person reviewing what they find.
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Shared measures
An agreed set of measures, each defined once, so every team works from the same numbers.
How we approach analysis
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Question first
We start with the decision better data would help you make, not with the tools.
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Honest about uncertainty
Forecasts show their ranges and assumptions, not just a single number.
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A person in the loop
AI-assisted findings are checked by an analyst before anyone acts on them.
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Clear to read
Charts and reports designed for the people who use them, in plain language.
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Repeatable
Analysis kept in version-controlled code, so it can be rerun and checked.
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Private
Personal data kept to a minimum, protected, and used only for the purpose agreed.
Technology we use
We'll suggest the simplest set of tools that does the job, and that your own team can live with after we're done.
Reporting
- Power BI
Analysis
- Python
- SQL
Data
- S3
- Redshift
- Snowflake
What you get
Everything your team needs to run it, change it and understand it.
- Dashboards and reports your teams use
- Agreed definitions for each measure
- Forecasts with their assumptions written down
- Analysis in version-controlled code
- Refresh schedules and alerts
- A handover session for your analysts
How a project runs
Nothing starts without your sign-off, and you'll see working software every two weeks.
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A free call
Thirty minutes to talk through what you need. If we're not the right fit, we'll say so.
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Discovery
A few short workshops to agree goals, users, constraints and what success looks like.
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Design
Screens you can click through and test with real users before we write any code.
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Build
Two-week sprints. Each one ends with a demo of working software you can try and comment on.
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Launch
Automated tests, security checks and a go-live plan with a way back if something goes wrong.
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Looking after it
Your system moves onto a Managed Services retainer, supported by the people who built it.
What happens after launch?
You can keep us on to look after it. The people who wrote the code are the ones who keep it running, so nothing gets lost in a handover.
Common questions
- Is our data good enough for AI?
- Sometimes not yet. We check its quality first and tell you plainly. Often the first win is simply reporting you can rely on.
- Can our own team maintain the dashboards?
- Yes. We build on tools your team can use, document the models and measures, and walk your people through extending them.
- How do you charge?
- Build work is billed by the hour against an estimate we agree before we start, and you see hours and progress every sprint. Looking after a live system is a monthly or yearly retainer.
- Where do we start?
- With a free 30-minute call. If we're not the right fit, we'll tell you. If we are, we agree goals and an estimate before any work begins.
Tell us what you're working on
The first call is free and there's no sales pitch. We reply within 24 hours.