Answers grounded in your knowledge.
Retrieval-based assistants, document drafting and summarisation that cite your own sources, with access controls and human review where it matters.
Practical intelligence: machine learning, generative AI and automation scoped around real decisions, your data and your risk tolerance.
AI that earns its place.
We build on established models and tools where they fit, and custom models where they don't.
Machine learning
Classification, forecasting and recommendation models trained on your data.
Generative AI
Assistants, drafting and knowledge tools grounded in your own content.
Predictive analytics
Forward-looking insight for demand, churn, risk and operations.
Intelligent automation
Workflows that combine rules, models and people.
AI integration
AI features added to the products and systems you already run.
Data preparation
Pipelines and quality checks that make data usable for models.
See what's coming.
Forecasts and risk scores built on historical data, explained clearly enough for teams to trust and act on them.
Less keying, more judgement.
Extraction, classification and routing that take repetitive work off people, while low-confidence cases go to a human by default.
Data that's ready to learn.
Pipelines, quality checks and governance that make your data dependable for analytics and AI — the foundation every model needs.
Start with the decision, not the model.
Small, measurable pilots that earn the right to scale. Read our scoping guide.
- 01
Frame
The decision or task, its users and how success is measured.
- 02
Assess data
Availability, quality, permissions and privacy constraints.
- 03
Pilot
A focused prototype tested against the baseline.
- 04
Integrate
Into real workflows, with monitoring and human review.
- 05
Improve
Feedback loops, retraining and expansion to new cases.
Where AI tends to help.
Lead scoring
Rank leads by likelihood to convert so teams focus first where it counts.
Document intelligence
Extract fields, classify and route incoming documents and requests.
Knowledge assistant
Help agents find accurate answers from your own content, faster.
Demand forecasting
Anticipate volumes for stock, staffing and capacity decisions.
Churn prediction
Spot accounts at risk early enough to act.
Hiring support
Summarise and organise candidate information for faster, fairer reviews.
Every AI/ML Solutions service.
Start with one service or combine several into a single programme. Each page explains the problems it solves, what you receive and how the work runs.
AI strategy & machine learning
AI Consulting
Use-case discovery, data readiness, build-or-buy advice and practical AI roadmaps.
Custom AI Development
Bespoke AI applications, models and integrations from prototype to production.
Machine Learning Development
Feature engineering, training, evaluation, MLOps and monitored deployment.
Deep Learning Solutions
Neural networks for images, text, audio and time series, trained and deployed efficiently.
Natural Language Processing (NLP)
Classification, extraction, sentiment, semantic search and summarization of text.
Computer Vision Solutions
Detection, inspection, classification, OCR and video analytics.
Predictive Analytics
Forecasting, churn and lead scoring, and risk models delivered where decisions happen.
Generative AI & automation
Generative AI Solutions
Assistants, knowledge tools and copilots built with evaluation, security and oversight.
Large Language Model (LLM) Solutions
Model selection, prompting, fine-tuning, private deployment and LLMOps.
Retrieval-Augmented Generation (RAG)
Ingestion, vector and hybrid search, permission-aware answers with citations.
AI Chatbot Development
Customer and employee chatbots grounded in your content, with human handover.
AI Agent Development
Tool-using agents that complete multi-step tasks with permissions and approvals.
AI Process Automation
AI-assisted workflows combining classification, extraction and rules with human review.
Intelligent Document Processing (IDP)
OCR, classification and extraction from invoices, forms and contracts, with review.
AI/ML questions.
How do we know if AI is right for our problem?
We start with the decision or task you want to improve, then check the data available and how success would be measured. If a simpler solution works better, we'll say so.
What about data privacy?
Data handling is agreed before any work starts: where data lives, who can access it and which services may process it. We design solutions to fit your policies and risk tolerance.
Do you build on existing AI models?
Where it makes sense, yes — combining established models with your own data and workflows is often faster and more reliable than training from scratch.
How long does a first use case take?
It depends on data readiness and scope. We usually recommend a short, well-defined pilot with clear success criteria before scaling up.
Turn complexity into clarity.
Bring the decision you want to improve. We'll help scope a pilot that can prove its value.