Coaches had 30 seconds between points, but insights took hours. Now, AI analyzes live telemetry to answer tactical questions courtside.
The organizer of the world's largest annual women's team competition manages live tennis events featuring over 140 competing nations.
Coaches have less than 30 seconds between points to make decisions, but critical gameplay insights historically arrived hours after matches ended....
“When data’s available consistently, it helps you quickly read key percentages and playing patterns (both ours and the opponents’) and supports tactical decision-making in a clear, immediate way.”
International Tennis Federation (ITF)'s Live match analytics is part of this use case:
Global governing body for world tennis and international tournament organizer.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Helped build the ingestion and transformation layer for ITF's Match Insights app on Azure.
Related implementations across industries and use cases
Data scattered across systems forced generic content. Now, AI agents surface personalized stats and videos via chat during live matches.
A one-second delay was too slow for live sports. Cloud inference now delivers stats 10x faster, powering 60+ AI initiatives.
Managing 200TB of player data required heavy manual oversight. Now, serverless pipelines let scientists deploy models themselves.
Custom analytics required months of full-stack development. Now, self-serve AI apps connect analysts directly to data models.
Manual media analysis and ad localization bottlenecked campaigns. Now, AI drafts insights and localizes assets for human refinement.
Agency fees bottlenecked operations. Now, 50+ custom GPTs handle tasks from turf analysis to invoicing, saving six figures annually.
Fans faced anxiety tracking high-stakes tickets across systems. Now, integrated AI instantly pulls order details, eliminating queues.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.
Coaches had 30 seconds between points, but insights took hours. Now, AI analyzes live telemetry to answer tactical questions courtside.
The organizer of the world's largest annual women's team competition manages live tennis events featuring over 140 competing nations.
Coaches have less than 30 seconds between points to make decisions, but critical gameplay insights historically arrived hours after matches ended....
“When data’s available consistently, it helps you quickly read key percentages and playing patterns (both ours and the opponents’) and supports tactical decision-making in a clear, immediate way.”
International Tennis Federation (ITF)'s Live match analytics is part of this use case:
Global governing body for world tennis and international tournament organizer.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Helped build the ingestion and transformation layer for ITF's Match Insights app on Azure.
Related implementations across industries and use cases
Data scattered across systems forced generic content. Now, AI agents surface personalized stats and videos via chat during live matches.
A one-second delay was too slow for live sports. Cloud inference now delivers stats 10x faster, powering 60+ AI initiatives.
Managing 200TB of player data required heavy manual oversight. Now, serverless pipelines let scientists deploy models themselves.
Custom analytics required months of full-stack development. Now, self-serve AI apps connect analysts directly to data models.
Manual media analysis and ad localization bottlenecked campaigns. Now, AI drafts insights and localizes assets for human refinement.
Agency fees bottlenecked operations. Now, 50+ custom GPTs handle tasks from turf analysis to invoicing, saving six figures annually.
Fans faced anxiety tracking high-stakes tickets across systems. Now, integrated AI instantly pulls order details, eliminating queues.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.