Impactful artificial intelligence and machine learning

Value not theory

MDRx has been designing and deploying AI and ML models for several years, realising real benefits for clients across a broad range of private and public sectors.

As an experienced AI consultant, we focus on outcomes, typically combining clients’ proprietary datasets with others that are publicly available to deliver real and bespoke value. We have deep expertise in natural language processing, financial modelling and machine vision leveraging our exceptional Data Scientists, Data Engineers and Software Engineers.

To ensure we deliver value not theory, our Product Managers and Strategists maintain a firm focus on the key problem(s) to be solved and ensure our AI and ML engines’ outputs and recommendations are actionable, relevant, and improve over time.

AI and ML are not without their ethical, legal and regulatory challenges. We work with experts from across The MDR Group to assess and mitigate risks associated with, for example, bias and discrimination, cyber security, data protection and intellectual property to ensure “compliance by design” in everything that we do.

Natural language processing
AI-powered assistants
Facial recognition
Fraud prevention
Computer vision
Behavioural analysis
ML pattern recognition
Recommendation systems
AI gaming
Real-time personalisation

What are AI and ML?

Artificial Intelligence (AI) refers to the simulation of human intelligence in machines, enabling them to perform tasks that typically require human intelligence, such as problem-solving, learning, decision-making, and language understanding. AI systems utilise algorithms and data to process information, identify patterns, and make predictions or recommendations.

Machine Learning (ML), a subset of AI, involves the development of algorithms that allow computers to learn from data and improve their performance over time without being explicitly programmed. In ML, models are trained on datasets, learning from examples to make predictions or decisions.

Harnessing the full potential of AI

The real benefit of adopting AI comes when business leaders look beyond the hype and meaningfully consider the AI strategies best suited to their organisation.

High-performing executive teams need to take a strategic lead and consider the realistic opportunities for a well-considered AI strategy to impact their organisation’s brand, top-line or bottom-line performance.


1. Data-driven insights and decision-making: AI and machine learning enable enterprises to extract valuable insights from large datasets, empowering them to make data-driven decisions, identify trends, and understand customer behaviours more effectively, leading to better strategic planning and improved business outcomes.
2. Process automation and efficiency: Automation of routine tasks through AI and machine learning increases operational efficiency. This allows employees to focus on more strategic tasks, reduces human errors, and accelerates workflows, ultimately leading to cost savings and improved productivity.
3. Personalisation and customer experience: AI-powered algorithms analyse customer data to provide personalised experiences, recommendations, and interactions. This enhances customer satisfaction, engagement, and loyalty by delivering relevant content, products, and services tailored to individual preferences.
4. Predictive analytics and forecasting: Machine learning algorithms can predict future trends and outcomes based on historical data. Businesses can use these insights to anticipate market shifts, optimise inventory levels, and plan resource allocation more effectively, resulting in improved decision-making and competitive advantage.


A data pipeline using machine learning for UK taxpayers UK's official archive and publisher department.

A data pipeline using machine learning for UK taxpayers

Empowering artists and streamlining music rights administration

Simplifying documentation using machine learning Amplifi assesses, simplifies, and audits regulated documents.

Simplifying documentation using machine learning