AI & Machine Learning
Predictive models, data science, and intelligent automation - from classical ML pipelines to production-grade AI systems processing millions of records.
AMT's AI & Machine Learning practice goes beyond chatbots and language models. We build production-grade predictive systems that ingest massive datasets, train robust models, and deliver actionable insights at scale - from climate analytics to computer vision.
Our data science team specialises in classical ML techniques - Random Forest, Gradient Boosting, Multi-output Classifiers - as well as deep learning with TensorFlow and PyTorch. We choose the right tool for the problem, prioritising model interpretability and deployment reliability over hype.
We handle the full ML lifecycle: data ingestion and cleaning, feature engineering, model training and evaluation, API deployment, and ongoing monitoring. Our pipelines are built to process millions of records efficiently using Python, Pandas, and scalable cloud infrastructure.
Whether you need demand forecasting, anomaly detection, recommendation engines, or domain-specific predictive models, our team delivers end-to-end solutions that integrate seamlessly with your existing technology stack.
The Client
A green-tech company offering carbon emission reduction plans to UK homeowners, helping them make their homes more energy-efficient and environmentally friendly.
The Problem
Homes are significant contributors to carbon footprints through inefficient energy usage. Generating accurate, personalised retrofit plans requires correlating massive datasets - building characteristics for 20 million UK properties, historical climate data spanning 1950–2023, solar irradiance, and flood risk - into a single actionable recommendation.
The Solution
- Built an AI model analysing 20M+ UK properties using parameters including building age, construction type, wall/roof/floor insulation, glazing, and heating systems.
- Integrated historical weather, climate, flood risk, and solar irradiance data from 1950–2023 to factor environmental context into retrofit recommendations.
- Developed a user-facing platform where homeowners enter a postcode to receive a tailored retrofit plan with specific energy-saving measures and projected savings.
- Implemented a premium tier connecting users with certified assessors, vetted contractors, and green lending partners to action their retrofit plans.
The Outcome
The platform delivers detailed, data-driven retrofit plans that enhance energy efficiency and contribute to sustainable, eco-friendly living - turning complex multi-source data into clear, actionable guidance for UK homeowners.
Technologies Used
// tech_stack
Core Technologies
Python / scikit-learn
Classical ML models - Random Forest, Gradient Boosting, and ensemble methods for structured data.
TensorFlow / PyTorch
Deep learning frameworks for neural networks, computer vision, and complex pattern recognition.
Data Pipelines
Pandas, Apache Spark, and ETL workflows for processing millions of records at scale.
Model Deployment
REST API serving, model versioning, and monitoring for production ML systems.
Need AI & Machine Learning expertise?
Let's discuss your project.