AI solutions
AI solutions that do useful work, measured on your own data
We find the tasks where AI saves real time or money, prove it on your data against a clear target, then build it into the tools your team already uses.
- Assistants that answer from your documents
- Document reading and data extraction
- Forecasting and analytics
- Computer vision for inspection and counting
- AI (this service)
- Reads delivery notes
- Forecasts reorders
- Answers staff questions
- Software
- Warehouse app
- ERP sync
- Stock dashboard
- Hardware
- Barcode scanners
- Wi-Fi and network
- On-site server
Data flows up: the devices feed the software, and the software feeds the AI.
Where AI helps
We start from the task, not the technology. These are the areas where AI most often pays for itself.
Assistants and chatbots
Answer customer or staff questions from your own documents and systems, show where each answer came from, and hand over to a person when needed.
Document processing
Read invoices, delivery notes, forms and contracts, extract the fields you need and pass them to your systems for checking.
Forecasting and analytics
Predict demand, spot unusual transactions and find patterns in your sales and operations data.
Computer vision
Count, inspect and read from camera images, for example spotting defects on a production line or reading labels and meters.
Workflow automation
Sort emails, tickets and requests, draft replies and fill in forms, with people approving what matters.
AI in your existing software
Add AI features to the applications you already use, with the monitoring and controls that keep them reliable.
How an AI project runs
- 1
Assess
We look at the task, the data you have and what success means, and tell you plainly whether AI is the right tool.
- 2
Prototype
We build a working prototype on your data and measure it against the target we agreed.
- 3
Put it into production
We integrate it with your systems, add monitoring and human review, and improve it as real use comes in.
Safeguards in every AI project
- Agreed rules for what data a model may see
- A choice of cloud or on-premises models
- Accuracy measured on your own examples
- People review the decisions that matter
- A log of every input and output
- Running costs estimated and monitored
Not sure where AI fits?
Start with an assessment. We review your processes and data and give you a short list of the opportunities worth pursuing, with the effort and benefit we expect for each, and the ones we'd advise against.
Frequently asked questions
Do we need a lot of data?
Often not. Current language and vision models can do useful work from your documents and a modest set of examples. The assessment tells you what your data can support.
Where is our data processed?
We agree that up front. Depending on sensitivity and cost, models run through a cloud provider under a data processing agreement, or on hardware in your own office or data centre.
How do you make sure it's accurate?
We agree a target before we start, measure the prototype on real examples from your business and keep measuring in production. Where mistakes are costly, a person reviews the output.
What does an AI project cost?
An assessment or a prototype is a small fixed-price project. The cost of going into production depends on the integration work and on usage, and we estimate running costs before you commit.
Find out where AI can help
Tell us about the task you have in mind, or ask for an assessment. We'll be straight about what AI can and can't do for you.