Where AI saves money in healthcare: diagnosis versus treatment
An analysis of the economics of artificial intelligence across the healthcare pathway, recognised with MDPI Healthcare’s 2022 best paper award.
Data engineering & analytics
Pipelines, data platforms and dashboards that make your data ready for AI.
Overview
Reliable data is what makes AI work. We build pipelines and data platforms on Azure, AWS and Databricks that bring scattered data together, keep it clean and governed, and present it in dashboards leaders actually use.
What we build
- Data pipelines
- Batch and streaming pipelines from your source systems, files and devices.
- Lakehouse platforms
- Modern data platforms on Databricks, Azure or AWS with clear ownership and access control.
- Data quality and governance
- Validation rules, lineage and cataloguing so people can trust the numbers.
- Decision dashboards
- Dashboards built around the decisions leaders make, not around the tables in the database.
Use cases by industry
Where data engineering & analytics makes the biggest difference for our clients.
Data engineering & analytics: case studies & projects
Filter all case studies
Machine learning and IoT for solar plant control and fault detection
A patented approach that combines IoT sensing with machine learning to control a solar plant, detect faults early and predict energy output.
Farm digital twin for yield forecasting and irrigation planning
A field-level digital twin built from satellite imagery, weather and soil data that forecasts yield and recommends when and how much to irrigate.
Credit risk scoring and early-warning signals for an NBFC
Machine-learning credit scores with clear reason codes, plus an early-warning model that flags accounts likely to fall behind on payments.
Grievance classification, prioritisation and routing
Machine learning that reads incoming citizen grievances, assigns category and urgency, and routes each one to the right office, with dashboards for senior officers.
How we deliver
Discover
A short workshop to understand the problem, the data and what success looks like.
Prototype
A working proof of concept on a sample of your data, so you can judge results early.
Build
The full solution, tested against your data and integrated with your systems.
Deploy and support
Production deployment on your cloud, with monitoring and continuous improvement.
Questions
Do we need a data platform before starting AI?
Not always. We often build the minimum pipeline a first AI use case needs, then grow it into a platform.
More technologies
Explore data engineering & analytics for your organisation
Start with a free discovery call. We will tell you honestly what is possible with your data.