Service
AI and Machine Learning
Applied AI that solves a defined business problem — from predictive models to LLM-powered assistants.
The business problem
Many AI initiatives stall at the demo stage: a model works in a notebook but never reaches the people who need it, or it cannot be trusted, monitored or maintained.
The outcome
AI features that are measurable, integrated into your existing tools, and designed to be monitored and improved after launch.
What we can build
- Forecasting, scoring and classification models
- Document and text understanding pipelines
- LLM-powered assistants grounded in your own data (RAG)
- Recommendation and personalisation features
- Model APIs that plug into existing applications
Typical deliverables
- Problem framing, success metrics and data assessment
- Baseline and iterated models with evaluation reports
- Model serving API or batch pipeline
- Monitoring for accuracy, drift and cost
- Documentation of data, assumptions and limitations
Relevant technologies
We choose tools to fit your requirements and existing stack. Commonly used:
- Python
- PyTorch
- scikit-learn
- LLM APIs
- Vector databases
- FastAPI
Engagement process
How we deliver AI and Machine Learning projects
A consistent, transparent process — with clear deliverables at every stage.
- 01 / 06
Discover
Understand the business problem, users, constraints and what success looks like.
- 02 / 06
Architect
Design the system, data flows and integrations, and choose a technology stack that fits.
- 03 / 06
Build
Develop in short, reviewable iterations with automated tests and regular demos.
- 04 / 06
Integrate
Connect the solution to your existing applications, data sources and devices.
- 05 / 06
Deploy
Release to production through automated pipelines with security and rollback in place.
- 06 / 06
Monitor & Improve
Track performance, reliability and usage, then iterate based on real-world data.
FAQ
Common questions
Relevant industry solutions
How do we know if AI is the right approach?
We start with the business problem and the data available. If a simpler rules-based or analytics solution is a better fit, we will recommend it.
What data do you need to begin?
A representative sample is enough for an initial assessment. We review quality, volume and access constraints before committing to a model approach.
Related services
Often combined with
Computer Vision and Video Analytics
Detection, counting and tracking systems that turn camera feeds and images into structured operational data.
Learn more about Computer Vision and Video AnalyticsData Engineering and Analytics
Reliable pipelines that collect, clean and model data from every source into one trusted foundation.
Learn more about Data Engineering and AnalyticsBusiness Intelligence Dashboards
Dashboards and reports designed around the decisions your team needs to make — not just the data you happen to have.
Learn more about Business Intelligence DashboardsReady to discuss your AI and Machine Learning project?
Tell us what you are trying to achieve. We will review it and come back with practical next steps — a scoped project, a feasibility check, or an honest recommendation.