Predictive analytics
We build machine-learning models that forecast outcomes your business cares about: next month's revenue, which customers are likely to leave, when a piece of equipment will need maintenance. The models run on your own infrastructure or on a managed cloud instance we set up for you.
What is included
- Data audit and feature engineering (we clean and structure the raw inputs your systems already generate)
- Model selection and training using gradient-boosted trees, time-series methods, or neural networks depending on the problem
- A REST API endpoint so your CRM, ERP, or spreadsheet can request predictions on demand
- Accuracy monitoring dashboard with automated alerts when model drift exceeds a threshold you set
- Quarterly retraining included for the first year
Typical timeline: four to eight weeks from kickoff to production, depending on data readiness. We have delivered forecasting systems for logistics firms, e-commerce retailers, and subscription software companies.
Workflow automation
Repetitive knowledge work is expensive and error-prone. We connect language models, optical character recognition, and rules engines to handle tasks like invoice matching, support ticket routing, document summarisation, and compliance checks.
What is included
- Process mapping workshop where we document each step, decision point, and exception path
- Custom automation pipeline built with Python, integrated into your existing tools via API or file-watch triggers
- Human-in-the-loop review interface for edge cases the model is uncertain about
- Detailed logging so you can audit every automated decision
- Three months of post-launch support and tuning
One financial services client reduced their monthly invoice processing time from 40 hours to under 5 hours. The system handles roughly 2,000 invoices per month and flags about 3% for manual review.
Custom dashboards and reporting
Dashboards fail when they try to show everything. We design focused views that answer the two or three questions each role actually asks every day. The data refreshes automatically, so nobody has to email a spreadsheet around on Monday mornings.
What is included
- Stakeholder interviews to identify the metrics each team needs
- Data pipeline connecting your databases, APIs, or flat files to a central warehouse
- Interactive dashboard built in a tool your team already knows (Metabase, Grafana, or a custom web app)
- Scheduled email digests for people who prefer a summary in their inbox
- Training session for your team so they can modify filters and add new charts without calling us
We typically deliver a first working version within two weeks. Iteration continues until every stakeholder confirms the dashboard answers their questions without needing to open another tool.
How a typical project runs
We follow the same four-phase structure for every engagement. It keeps scope clear and gives you a working deliverable as early as possible.
Discovery
Two-week sprint. We audit your data, map the business process, and build a rough prototype. If the prototype does not show clear value, you owe nothing for this phase.
Build
We develop the production system in two-week increments, demoing progress at the end of each. You can steer priorities between increments.
Launch
We deploy to your environment, run parallel testing alongside your existing process, and train the team that will use the system daily.
Support
Post-launch monitoring, model retraining, and bug fixes. Support packages run in three-month or twelve-month blocks.
Engagement options
We offer three ways to work together. All prices exclude VAT.
Discovery sprint
Two weeks, fixed price
- Data quality audit
- Process mapping document
- Working prototype
- Written recommendation report
Project engagement
Scoped per project
- Full build and deployment
- Team training session
- 90 days post-launch support
- Source code and model ownership
Retained partnership
Ongoing, cancel with 30 days notice
- Dedicated engineer allocation
- Continuous model monitoring
- Priority response within 4 hours
- Quarterly strategy review