Fragmented systems bottlenecked model updates. Automated pipelines cut infrastructure work 90% and sped up deployment 20%.
The world’s most accurate forecaster delivers 25 billion daily predictions to 2 billion people, helping global businesses and consumers make critical weather-dependent decisions.
Erratic weather patterns demanded faster forecast updates, but a fragmented container-based environment caused significant lag times between model...
“Building weather and climate resilience is a global challenge that requires working together with other experts in the weather community and across industries, such as AWS, NVIDIA, and more. We continue to innovate with cutting-edge technologies including generative AI to improve communications, messaging, and alerting of those forecasts. Because even the freshest, most accurate forecast can only be helpful if it gets in front of those who need it most during a weather event.”
Weather data and forecasting platform for aviation, media, and enterprise sectors.
Cloud computing platform and on-demand infrastructure services.
Related implementations across industries and use cases
Staffing 26 regional weather teams was cost-prohibitive. AI now scripts and voices 78 daily updates without human intervention.
Researchers were stuck maintaining hardware. Moving to managed infrastructure freed them to build and cut training costs by 90%.
Manual research took weeks per product. Gen AI now automates analysis across portfolios, driving a 21% revenue surge.
Researchers were stuck maintaining hardware. Moving to managed infrastructure freed them to build and cut training costs by 90%.
250M+ uploads lacked tags, limiting search. AI now auto-generates metadata, cutting churn by 7% and boosting sign-ups by 7%.
Sifting through 1,200 clips manually took hours. AI search now locates shots instantly, cutting production timelines by 30%.
Scattered, multilingual HR files were a manual bottleneck. Non-technical staff built 10 AI agents to locate, translate, and format them.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.
Lab supply orders were handwritten in notebooks. Digital ordering now takes seconds, saving 30,000 hours for research annually.