AI and machine learning

Practical AI, built into software people use.

We help growing businesses use AI for specific, measurable jobs: reading documents, answering questions from their own data, automating repetitive work and checking images. We build it into the systems you already have, and we will tell you when AI isn't the answer.

Talk about an AI project What we build

01 What we build

Six kinds of AI work we take on

01

Assistants over your own documents

A chat assistant that answers staff or customer questions from your policies, manuals and product data, with links back to the source so answers can be checked.

02

Document and invoice extraction

Read supplier invoices, delivery notes, forms or CVs and turn them into clean data in your system, with a person reviewing anything the model isn’t sure about.

03

Workflow automation

Connect the tools you already pay for so orders, emails, spreadsheets and approvals move on their own instead of being copied by hand.

04

Computer vision

Face verification, image checks and visual inspection. We run face verification in production in our own HRMS.

05

Forecasting and analytics

Dashboards and simple forecasts for sales, stock and staffing, built on the data you already have.

06

AI consultancy

An honest look at where AI would pay for itself in your business, and where a simpler fix would do the job better.

02 In production

Face verification in our own HRMS

When a member of staff clocks in on the mobile app, our face service compares their photo with the face they enrolled, and the attendance is recorded only if the match passes. It can also check that they are inside a location fence around their workplace.

Under the hood it is a FastAPI service running InsightFace face-recognition models on ONNX Runtime, with OpenCV for image handling. Every attempt is logged with the confidence score that produced the decision, so a manager can see why a check passed or failed.

03 How we work

Small, measurable steps

01

Start with the job

We pick one task that costs you time or money today, and agree how we will measure whether the AI does it better.

02

Prove it on your data

A small working prototype on a sample of your real data, before you commit to a full build.

03

Keep people in charge

Low-confidence results go to a person to approve. Every decision the system makes can be traced and explained.

04

Look after your data

Personal data is handled in line with UK GDPR, with clear choices about which AI providers see what, or keeping models on your own servers.

04 Questions

Common questions about AI projects

Do we need a lot of data to use AI?

Often not. Many useful tools, such as document extraction or an assistant over your own manuals, work with the documents you already have. We check what you have during discovery.

Will our data be used to train someone else’s model?

Not if you don’t want it to be. We choose providers and settings that don’t train on your data, or run open models on infrastructure you control.

Can you add AI to software we already have?

Usually, yes. Most of our AI work plugs into an existing system through its API or database rather than replacing it.

What does an AI project cost?

It depends on the job. We start with a fixed-price discovery and prototype, so you know whether it works before you spend more.

Got a job you wish a computer would do?

Describe it in a few lines. We'll tell you honestly whether AI can help and what it would take.

Book a discovery call