Services

AI integration services.

We connect AI models to the systems you already run, so the technology does real work instead of sitting in a demo nobody uses twice.

Connected to your own systemsScoped to one real taskBuilding since 2016
The problem

Most AI projects stall at the demo.

The pilot impresses everyone in the room, then never reaches the people doing the work, because it was never connected to anything.

It starts with the tool, not the task

Somebody picks a model first and then goes looking for a job it can do, which is the wrong way round.

It never reaches the workflow

If people have to leave the system they work in to use it, they will use it twice and then stop.

Nobody checked the output

Without a review step and a way to catch mistakes, one confident wrong answer costs more than the tool saved.

What is included

What an AI integration covers.

Scoped to a task with a measurable before and after.

Use case scoping

Finding the task where judgement is needed and volume is high, then ignoring the ones that sound impressive but save nothing.

Integration

Connected into the tools your team already opens, rather than living in a separate tab they have to remember.

Review and guardrails

A human check where the cost of being wrong is high, and limits on what the system is allowed to do alone.

Measurement

Time or cost measured before and after, so you can tell whether it earned its keep.

How it runs

Three steps, no mystery.

One task, done properly, before anything wider.

1

Find the task

Where your team spends time on judgement calls that follow a pattern, and what being wrong would cost.

Before any tool is chosen
2

Build and check

Built into the existing workflow and run in parallel, so you can compare its output against what your team would have done.

Run alongside the humans
3

Hand over

Documented, with the guardrails explained, so your team can adjust it without us.

Yours afterwards
Questions

Before you brief an AI project.

What people ask before putting AI into a business process.

Tasks with high volume, a clear pattern and a tolerable error rate. Summarising, drafting, classifying and routing tend to work. Anything where one wrong answer is expensive needs a human check, which changes the maths.
That gets decided before anything is built. Which data the system sees, where it is processed and what is retained are scoping questions, not details to settle afterwards.
Automation follows rules you can write down. AI handles the tasks where the rules are too fuzzy to specify. Plenty of projects need both. See the business process automation page.
It will, sometimes. That is why we scope where a human reviews output and where the system is allowed to act alone. A project without that distinction is not ready to go live.
Free, and useful whether or not you hire us

Tell us the task, not the tool.

One call. We will tell you whether AI is the right answer for it, or whether plain automation does the job cheaper.

No pitch deck No obligation A real person