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AI & Data

AI & Machine Learning

We develop AI features around a defined decision or user need, with realistic data requirements, evaluation criteria and operational controls.

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About this service

Built around the work, not a template.

AI projects work when the problem, data and measurement approach are explicit. We establish a baseline and evaluation loop before expanding scope.

Key deliverables

  • Use-case and data feasibility assessment
  • Model or provider evaluation
  • Prototype and benchmark
  • Production integration
  • Evaluation and monitoring framework

How we work

A clear path from context to delivery.

01

Define

Specify what the system should assist with and how output will be judged.

02

Assess data

Review availability, quality, permissions and examples.

03

Evaluate

Compare approaches against a baseline and edge cases.

04

Integrate

Add controls, feedback and monitoring.

Practical outcomes

  • Evidence before a large AI investment
  • Clear boundaries for automated and human decisions
  • A process for tracking model behavior

Capabilities and approach

Prediction and classificationRetrieval-augmented generationModel and API integrationEvaluation datasets

Service questions

Useful details before we begin.

It depends on the use case and whether an existing model can be adapted.