Our AI Tech


A technology platform and process optimised to handle scale and complexity to deliver commercial value through the application of a tailored AI solution that matches every customer need.

Data Operations Stack


For data collection, storage and transformation to support analytics and machine learning use cases, and ensure compatibility and scalability

Machine Learning Operations Stack


Supports model development and collaboration, model deployment and reporting

Data Science Process


Outlines best practices for tool selection, procedures, checkpoints, handovers, model evaluation, model iteration and technical skills

For data collection, storage and transformation to support analytics and machine learning use cases, and ensure compatibility and scalability

Supports model development and collaboration, model deployment and reporting

Outlines best practices for tool selection, procedures, checkpoints, handovers, model evaluation, model iteration and technical skills

Flow diagram of steps

Step 1
Data Ingestion

Following integration with a number of sources, captures up to tens of billions of daily events across the globe.

Step 2
Data Prep

Prepares the dataset to build the AI models (known as “extraction, transformation and loading” or “ETL”)

Step 3
Model Building

Builds, evaluates and tunes a number of potential AI models

Step 4
Deploy Models

Deploys the best performing model(s) with up to real time model updates

Step 5
Reporting

Logs both model and commercial KPIs, feedback into Step 1 for a continuously learning process

Our chosen technology providers


Logo for AWS
Logo for Databricks
Logo for Scikit
Logo for Apache Airflow
Logo for Pandas
Logo for K8s
Logo for Docker
Logo for Jupyter
Logo for Google cloud
Logo for Python
Logo for Tensorflow
Logo for Dopamine
Logo for SpaCy
Logo for SciPy
Logo for NumPy

Get in touch to find out more about our tech

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