Our services in detail
AI readiness assessment
Before spending money on models or software, you need to know whether your data, systems and team are ready. This two-day on-site (or remote) assessment gives you that answer.
One of our consultants reviews your data sources, talks to the people who use them daily, and maps your current workflows. You receive a written report within five working days covering:
- Data quality score for each major dataset (completeness, consistency, freshness)
- A list of processes ranked by automation potential and expected time savings
- Gaps in infrastructure or skills, with specific recommendations to close them
- A rough budget estimate for the top three opportunities
The assessment costs £1,800 as a standalone service. If you proceed to a model development project within 60 days, we deduct the assessment fee from the project price.
Custom model development
This is the core of what we do. We build machine learning models trained on your data to solve a specific business problem. Common examples include:
- Sales forecasting: predict weekly or monthly revenue by product line, region or channel
- Churn prediction: identify subscription customers likely to cancel in the next 30 days
- Defect detection: classify product images from a production line as pass or fail
- Document classification: route incoming emails or PDFs to the right department automatically
Each model is delivered as a REST API endpoint hosted on your cloud account (AWS, Azure or Google Cloud). We include integration documentation, a testing suite, and a monitoring dashboard that alerts you if model accuracy drifts below an agreed threshold.
Typical timeline: eight to twelve weeks from data handover to production deployment. We hold a weekly 30-minute progress call throughout.
Process automation
Sometimes you do not need a custom model at all. You need the right connections between existing tools so data flows without anyone copying and pasting. We build these automations using a combination of APIs, scripting and, where appropriate, pre-trained AI services for tasks like optical character recognition or language translation.
Recent automation projects we have delivered:
- Extracting line items from PDF invoices and posting them into Sage 200
- Sorting inbound customer emails by topic and urgency, then assigning them to the right support queue in Zendesk
- Pulling daily stock levels from a warehouse management system and updating a Shopify store automatically
These projects are usually smaller and faster. Most are complete within four to six weeks. We provide a runbook so your IT team can troubleshoot without calling us.
Conversational AI and chatbots
We design and deploy chatbots that handle real customer questions, not the kind that loop you back to a menu. Our bots are built on large language model APIs and grounded in your own knowledge base: product catalogues, FAQ documents, policy manuals.
The bot runs on your website, WhatsApp or Microsoft Teams. It answers questions using your approved content and escalates to a human agent when it cannot help. We train it on your historical support tickets so it learns the phrasing your customers actually use.
Setup takes about six weeks, including two rounds of user testing with your support team. After launch we monitor accuracy for 90 days and retrain the model if needed.
Ongoing support and model maintenance
Machine learning models are not set-and-forget. Customer behaviour changes, product ranges shift, and data distributions drift over time. Our support plans include quarterly model retraining, performance reporting and priority access to our engineering team for bug fixes or feature requests.
We offer three support tiers (Essentials, Professional and Enterprise) described in detail on our pricing page. The Essentials plan covers most small businesses; Professional adds a dedicated account manager and faster response times.
How a typical project runs
Every engagement follows the same five-stage process. The length of each stage varies with the project, but the order stays the same.
1. Discovery call (free, 30 minutes)
We listen to your problem, ask about your data and systems, and give you an honest first opinion on whether AI is the right tool. If it is not, we will suggest alternatives.
2. Scoping and proposal (one to two weeks)
We write a fixed-price proposal describing the deliverables, timeline, data requirements and acceptance criteria. You review it, ask questions, and sign when ready.
3. Data preparation (two to four weeks)
We clean, transform and label your data. This is often the longest stage. Messy data is normal; we have dealt with hand-typed spreadsheets, scanned PDFs and databases with 15 years of inconsistent formatting.
4. Model development and testing (three to six weeks)
We train candidate models, evaluate them against your acceptance criteria, and iterate until performance meets the agreed threshold. You see results at every weekly check-in.
5. Deployment and handover (one to two weeks)
We deploy the model to your environment, run integration tests with your team, deliver documentation and conduct a training session. The 90-day support window begins on deployment day.
Technologies we work with
We are not tied to a single vendor. We pick the tool that fits the problem and your existing infrastructure. Here are the platforms and frameworks we use most often.
Python
TensorFlow
PyTorch
AWS
Google Cloud
Azure
We also integrate with business tools including Microsoft 365, Google Workspace, Xero, Sage, Shopify, Zendesk and Slack. If your tool has an API, we can connect to it.