Machine Learning & MLOps
Production-Grade
ML Solutions
From research to revenue: ML systems that deliver measurable business outcomes. We build, deploy, and operate machine learning at enterprise scale.
Schedule a ConsultationWhat We Deliver
End-to-end ML capabilities from experimentation to production, with the operational rigour enterprises demand.
ML Model Development
From classical machine learning to deep learning and LLMs, we develop models that are optimised for your specific data, latency requirements, and accuracy targets.
MLOps & Model Monitoring
Automated training, deployment, and monitoring pipelines. Drift detection, performance dashboards, and retraining triggers that keep models reliable in production.
Feature Stores
Centralised feature management that eliminates training/serving skew, accelerates experimentation, and ensures feature consistency across teams and models.
A/B Testing Frameworks
Statistically rigorous experimentation platforms for model comparison, canary deployments, and gradual rollouts with automated significance testing.
Our Approach
A disciplined ML lifecycle that reduces time-to-production while maintaining scientific rigour.
Problem Framing
Define the business problem as an ML problem. Establish success metrics, baseline performance, and feasibility assessment.
Data Preparation
Data collection, cleaning, feature engineering, and labelling pipelines. Ensure data quality and representativeness for training.
Model Development
Iterative experimentation with tracked experiments, hyperparameter tuning, and model selection based on business-relevant metrics.
Production Deployment
Containerised model serving with CI/CD, automated testing, shadow deployments, and gradual traffic shifting.
Continuous Improvement
Ongoing monitoring, drift detection, automated retraining, and performance reviews to maintain and improve model quality.
Technologies We Use
We work with the best tools in the ML ecosystem, selecting the right platform for each use case.
Use Cases
ML systems we have built and deployed for enterprise clients.
Predictive Analytics
Demand forecasting, customer lifetime value prediction, and risk scoring models that integrate directly into business workflows and decision systems.
Forecasting · ScoringRecommendation Systems
Personalisation engines using collaborative filtering, content-based, and hybrid approaches for product recommendations, content curation, and search ranking.
Personalisation · RankingAnomaly Detection
Real-time anomaly detection for fraud prevention, cybersecurity, and operational monitoring, using statistical and deep learning approaches.
Fraud · Security · OpsNLP at Scale
Large-scale text classification, summarisation, and entity extraction pipelines processing millions of documents with transformer-based architectures.
NLP · TransformersWhy GIS Analytics
London-Based
Headquartered in London. We work on-site, hybrid, or fully remote to suit your team's needs.
Enterprise Clients
Work delivered for teams across telecoms, higher education and the charity sector, in London and across Europe.
Full-Stack Delivery
From data preparation through model development to production serving and monitoring -- we own the full ML lifecycle.
Ready to Get Started?
Let's put ML to work
for your business
From problem framing to production monitoring -- we partner with enterprises to build ML systems that deliver measurable ROI.
Schedule a Consultation