Our Artificial Intelligence services

Below is a plain description of what each service involves, what you get at the end, and roughly how long it takes. No jargon, no vague promises.

Custom model development

What this covers

We build machine-learning models tailored to a specific business problem you define. That could be predicting which customers are likely to churn next quarter, classifying product defects from factory-floor photographs, or extracting structured data from scanned contracts.

The work starts with an exploratory data analysis where we assess your dataset for quality, volume, and relevance. We then select an appropriate algorithm family, run experiments, and iterate until the model meets agreed accuracy targets. The final deliverable is a production-ready model exposed as a REST API, along with documentation your developers need to integrate it.

  • Exploratory data analysis report (week 1)
  • Baseline model with benchmark metrics (week 2-3)
  • Optimised model with hyperparameter tuning (week 3-5)
  • Deployed API endpoint with monitoring dashboard
  • Technical handover session for your engineering team
Neural network visualisation

Process automation

What this covers

Many office tasks involve reading a document, copying numbers into a spreadsheet, and sending a confirmation email. These tasks are predictable enough for a language model or a rule engine to handle reliably, but too variable for a simple macro.

We map your existing workflow step by step, identify where automation will save the most time, and build connectors between your tools. A typical automation project integrates with systems like Xero, Salesforce, SharePoint, or custom ERP platforms via their APIs. Where no API exists, we use browser automation or OCR as a fallback.

One recent project for a property-management firm automated tenant-reference checks. The system reads incoming PDF applications, extracts key fields (income, employer, previous addresses), runs them against a credit-check API, and generates a summary report. Processing time dropped from 25 minutes per application to under 90 seconds.

  • Workflow mapping and bottleneck analysis
  • Proof-of-concept automation for the highest-impact task
  • Full build with error handling and retry logic
  • Staff training (recorded video walkthrough included)
Automated workflow on office monitors

AI strategy consulting

What this covers

Before spending money on model development, it helps to know whether machine learning is the right tool for your problem. Sometimes a well-designed SQL query or a simple rules engine will do the job faster and cheaper. Our strategy audit answers that question honestly.

We interview stakeholders across your organisation, review your data infrastructure, and produce a written report that ranks potential AI use cases by expected return on investment and implementation difficulty. Each use case includes a rough timeline, resource requirements, and the risks involved.

The audit runs over two weeks. In the first week we conduct interviews and review data samples. In the second we write the report and present it to your leadership team. The fee is fixed and agreed before we start, so there is no risk of scope creep.

  • Stakeholder interviews (up to 8 sessions)
  • Data infrastructure review
  • Prioritised use-case roadmap (written report, 15-25 pages)
  • Executive presentation with Q&A
Strategy presentation in a meeting room

How a project typically runs

Every engagement follows the same four-phase structure, though the length of each phase varies by project size.

Discovery

We meet (in person or on a video call) to understand the problem, review available data, and agree on success criteria. This phase is free and usually takes one to two hours.

Scoping

We write a statement of work that lists deliverables, timelines, and costs. You review it, ask questions, and sign only when you are comfortable. No deposit is due until this document is agreed.

Build

The engineering work happens here. We send weekly progress updates with demo links so you can see the model or automation in action before it goes live. Feedback loops are short: if something needs changing, we adjust the same week.

Handover

We deploy to your infrastructure, run a technical walkthrough with your team, and hand over all code and documentation. The 30-day free support window starts on the day of deployment.

Ready to talk about your project?

Tell us what you are trying to solve and we will let you know whether we can help, usually within a day.

Get in touch