Data Studio Tech

02 / Implementation

From messy systems to useful capability.

Build the data foundation plus the key reporting, analysis and operational tools around it. Start where the value is. Continue into predictions, agents and custom products when they earn their place.

Typical delivery6–10 weeksDiscuss an implementation

A connected path

One system. More room to build.

  1. 01Source system
  2. 02Pipeline
  3. 03Model
  4. 04Analysis
  5. 05Machine learning
  6. 06Agent
  7. 07Internal application

The work can stop at a trusted model or continue all the way into machine learning, an agent or an internal application. The right endpoint depends on the problem.

Implementation modules

Four modules. One practical foundation.

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Layered data foundation illustration connecting business systems
01 / 04

Data foundation

Make the company's data usable.

Connect core systems and create a reliable commercial data environment that becomes the foundation for everything else.

The outcomeOne trusted data layer instead of multiple competing versions of the truth.

Typical workData pipelines · APIs · warehouses · data models · metric definitions · customer views · marketing, subscription and operational data · data quality

From £10kPart of a 6–10 week implementation
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Three coloured paths combining into a clear decision route
02 / 04

Decision tools

Turn data into something the business can actually use.

Build the decision tools, analysis, workflows and lightweight applications your team needs to make better decisions.

The outcomeLess manual analysis and faster answers to important business questions.

Typical workCommercial reporting · KPI systems · automated insight · dashboards · inventory tools · customer analysis · internal applications · data capture · workflow automation · synthetic research

From £10kPart of a 6–10 week implementation
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Predictive intelligence illustration showing signals converging on a target
03 / 04

Predictive intelligence

Use what has happened to anticipate what happens next.

Where predictive modelling creates genuine value, add focused machine-learning capability to the data foundation.

The outcomeMove from understanding the past to acting on what is likely to happen next.

Typical workCustomer segmentation · churn · propensity · lifetime value · forecasting · recommendations · demand prediction · anomaly detection · predictive and synthetic attributes

From £10kTypical delivery: 6–10 weeks
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AI analyst illustration connecting reporting, data and conversation
04 / 04

AI analyst

Give your team a practical AI interface to the business.

Build AI systems that work with your actual commercial data, definitions and business context, rather than generic chatbots.

The outcomeTeams can investigate performance and surface insight without waiting for another query or report.

Typical workNatural-language data analysis · MCP interfaces · management summaries · Slack and Teams assistants · analytical agents · business-specific tools · guardrails and controlled data access

From £10kTypical delivery: 4–8 weeks
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Built to fit

We build the minimum data system the business needs, then keep going where it helps.

No platform for the sake of it, and no forced leap into AI. Each layer is grounded in actual business definitions, accessible to the people who need it and designed to support the next decision.

Project scope

A focused build, shaped around a valuable use case.

Implementation modules start from £10k. Most delivery takes 6–10 weeks, depending on the scope and the systems involved.

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