AI implementation

Practical AI for research, data analysis and software delivery, with clear checks and human oversight.

  • Data analysis & research
  • Workflow integration
  • Coding pipelines

We help organisations put AI to work in defined, useful parts of their business: analysing information, supporting research and improving how software is delivered.

The work is in the whole process: selecting the inputs, connecting the tools, checking the output and deciding where people need to review it.

Customer data and research

Our experience includes work for a UK national newspaper as early as 2024, using Gemini Flash to analyse customer data and corroborate findings through online research.

That work informs a practical approach to AI-assisted analysis: bring relevant information together, distinguish source evidence from model inference, and make the results useful to the people working with them.

AI in existing workflows

We start with a specific task and the systems around it. What information is available? What should the output look like? How will the team know whether it is useful?

From there, we can help shape an implementation that connects models to existing tools and services, with explicit checks for incomplete inputs, uncertain results and failed steps.

AI-assisted software delivery

Our work also includes building pipelines for AI coding agents: connecting prompts, command-line steps, checks and human review into repeatable development workflows.

This includes orchestration across multiple steps and sessions, managing the context agents need, and preserving workflow state so work can be inspected and resumed. The focus is on a process that makes generated changes reviewable and fits around the team's development practices.

Evaluation and human oversight

An implementation needs a way to judge its output. We define what a useful result looks like, how it should be checked and when a person needs to make the decision.

Data access, handling and retention are part of that design. So are the practical trade-offs between model capability, response time and running cost.

Where to begin

A bounded workflow gives us something concrete to assess. We can help identify a suitable task, build an initial implementation and establish the checks needed before expanding its role.