Wholesale distributor, Midlands
Demand forecasting model replaced a spreadsheet-based process. Stock-outs dropped and over-ordering fell within the first quarter of use.
Stock-outs down 34%Your data already knows the answer. Our AI software asks the right question.
We build custom machine-learning models and automation pipelines for mid-size companies across England. No off-the-shelf dashboards, no vague "insights." You get software that does a specific job, measured by a number you actually care about.
Show me what my data can do
127Models deployed since 2021
14 daysAverage proof-of-concept delivery
91%Clients move past pilot stage
£2.3MSaved for clients last year
The problems we actually solve
Most AI pitches start with technology. We start with a frustration you already have.
Manual data wrangling eats 20+ hours a week
Your team copies numbers between spreadsheets, reformats CSVs, and chases colleagues for updates. The report is always late.
Automated ingestion and cleaning pipeline
We write connectors to your existing systems, standardise formats on arrival, flag anomalies, and push a clean dataset into your BI tool every morning at 06:00.
Forecasts rely on gut feeling
Demand planning, staffing rotas, stock orders: someone experienced "just knows." When they leave or get it wrong, the cost is real.
Predictive models trained on your history
We train time-series models on two to five years of your own records. The model outputs a forecast with confidence intervals, updated weekly, accessible via a simple web dashboard or API endpoint.
Customer questions overwhelm your support inbox
Eighty percent of inbound tickets ask the same fifteen questions. Your agents spend their time copying and pasting template replies.
Retrieval-augmented chatbot on your own docs
We index your knowledge base, FAQs and product manuals. The chatbot answers accurately from those sources, hands off to a human when confidence is low, and logs every interaction for review.
Four steps from messy data to working software
Every engagement follows the same structure. Timelines vary, but the sequence doesn't.
1
Scoping call
A 45-minute video call where we map your data sources, define the target metric, and agree on what "done" looks like. No charge.
2
Data audit
We connect to a sample of your data, profile it for quality, and write a short feasibility report. This takes five working days and costs a flat £950.
3
Proof of concept
A working prototype on real data, delivered in roughly two weeks. You test it, we iterate. If the numbers don't hold up, you walk away.
4
Production deploy
We harden the model, set up monitoring, write documentation, and hand over. Ongoing support is available on a monthly retainer or pay-per-incident.
What the numbers looked like afterwards
Three recent projects, anonymised per client request.
Private dental group, South East
Appointment no-show predictor flagged high-risk bookings 48 hours ahead. The front-desk team used the alerts to send targeted reminders and fill gaps.
No-shows cut by 41%
SaaS company, remote team
Retrieval-augmented chatbot handled first-line support queries, pulling answers from 1,200 help articles. Average first-response time shrank from 4 hours to under 90 seconds.
Response time −96%Questions we hear often
Do we need a data science team in-house?
No. We handle model development, deployment and monitoring. You need someone who understands the business problem and can evaluate results, but that person doesn't need to write code. Many of our clients designate a product manager or operations lead as the main contact.
What if our data is messy or incomplete?
That is the normal starting point, not the exception. The data audit in step two exists precisely to quantify gaps. Sometimes we can work around missing fields by engineering proxy features. Other times we recommend a short data-collection phase before modelling begins. We will be honest about which scenario applies.
How much does a typical project cost?
The data audit is £950 flat. Proof-of-concept builds range from £4,000 to £12,000 depending on complexity. Production deployments sit between £15,000 and £45,000 for most mid-size projects. We quote fixed prices after the audit, not open-ended day rates.
Where does our data go?
All processing happens on UK-based cloud infrastructure (AWS eu-west-2 by default, Azure UK South on request). We never share client data with third parties. After project completion, we delete all copies within 30 days unless you ask us to retain them for ongoing support.
Can you integrate with our existing tools?
Usually yes. We have built connectors for Salesforce, HubSpot, Xero, various SQL databases, Google Sheets, and a handful of niche ERP systems. If your tool has an API or supports CSV export on a schedule, we can work with it.
Start with a conversation
Tell us what is frustrating you. We will reply within one working day with an honest assessment of whether AI is the right tool.
