Deploying one model took four months of manual extracts. Teams now code directly on data, shipping in days to help at-risk users.
Britain’s largest generator of zero-carbon electricity, supplying gas and power to homes and businesses across the U.K.
Data scientists struggled with a self-built platform where obtaining data extracts took days and governance hurdles blocked progress. The team spent...
“Previously, we didn’t have good access to data or a way of deploying our models into production. We have a lot of very sensitive data, so we found it hard to do anything without sign-off and meetings. For every project, we had to ask the data lake team to provide extracts for us to work with, which could take days. It was slow-moving and difficult at times, and came with a lot of complexity, as we then had to manage the security and governance of that data ourselves.”
Integrated electricity utility producing and distributing low-carbon energy.
Cloud-based data warehousing, processing, and analytics platform.
Related implementations across industries and use cases
Silos trapped data across 15 countries. Now, teams forecast hourly energy demand and personalize offers for 10M households.
Bespoke solutions for 12B daily signals ballooned costs. A unified layer now reuses algorithms to deploy products across markets.
Forecasting required training a model for every single account. Now, a unified ML model predicts for 1M+ customers in minutes.
Permit teams drowned in 5,000 monthly requests across fragmented sites. Agents now navigate the web maze to process tasks in 2 minutes.
Service gaps left rural areas behind. AI agents now guide 9M users through 44 tasks on WhatsApp, unifying fragmented support.
Seven analysts manually wrote notes for 200 products. AI agents now digest fact sheets to draft compliant commentary instantly.
Forty entities duplicated work, stalling claims for days. A global AI engine standardized workflows, cutting settlement time to one day.