AI implementation

AI implementation, from first idea to daily use.

You bring the business problem. We help define a useful first version, build it around your tools and prepare your team to use it. Every project starts with a clear scope.

Talk about your project

Start here

What should an implementation actually change?

A successful first project has a specific outcome: fewer manual handovers, a more reliable follow-up process or less time spent finding information. “Use more AI” is not a useful acceptance test on its own.

We first map the current process with the people who use it. We identify the trigger, data sources, decisions, exceptions and owner. Then we decide which steps need fixed rules, which may benefit from AI and which should stay with a person.

The project

Four stages, with decisions you can see.

1. Define the scope

Agree the problem, systems, users and boundaries. Establish a baseline and decide what evidence will show that the first version is useful.

2. Build and connect

Implement a small, complete workflow. Configure access, map fields between systems and show your team realistic examples before expanding the scope.

3. Test and hand over

Exercise missing fields, duplicates, wrong inputs and unavailable services. Agree sign-off, document the workflow and explain how to pause it or handle exceptions.

After launch, the fourth stage is review: compare the result with the baseline and decide what to refine. Monitoring, maintenance and further changes depend on the support arrangement agreed for the project.

Before launch

A working demo is only part of the job.

Ownership: someone is responsible for the workflow and the exceptions it produces.
Access: each connection uses the permissions it needs, with agreed responsibility for accounts and credentials.
Approval: your team knows which actions run automatically and which wait for a person.
Recovery: failures are visible, and there is an agreed way to retry, pause or use a manual process.
Handover: documentation and training cover how the system is actually used.

Scope and cost

What affects the size of a project?

The number of systems is one factor. Data quality, access restrictions, unusual cases, approval rules and the amount of custom software can matter just as much. A simple connection between two well-maintained systems is a different project from rebuilding an inconsistent process across several teams.

We set out the build scope, timescale and cost before implementation. Third-party subscriptions, usage-based AI costs and ongoing support should be considered separately so you can understand the running cost as well as the initial work.

To prepare for a conversation, bring the names of your tools, a description of the recurring task and a sanitised example of the information involved. Please do not send passwords or sensitive customer records in an initial enquiry.

Let’s talk

Let’s define a useful first version.

Tell us where work gets held up, which tools you use and what a better result would look like. We’ll discuss the practical options and agree a scope before any build starts.

Discuss an automation project