Mentioned in 12 AI use cases across 8 industries
This is like giving clinical trial teams a very smart assistant that can instantly read through trial documents, data tables, and reports, then summarize findings, highlight safety issues, and draft analysis text so humans don’t have to do all the slow, manual reading and writing themselves.
Think of this as building your own ‘Netflix-style’ recommendation brain: it watches what each user does, learns their tastes, and then uses a mix of traditional recommendation models and modern generative AI to decide what to show or suggest next.
This is like giving a football club’s scouting department a super‑assistant that has read every match report, watched all the stats, and can instantly summarize which players fit the coach’s style and why.
This is like a smart, always-available hospital receptionist that understands what patients need, checks doctor calendars, insurance rules, and clinic constraints, and then finds and books the best possible appointment slot automatically.
This is like having an AI assistant watch a live TV channel or livestream for you and take notes in real time—who is speaking, what’s being said, topics, scenes, and key moments—so people and systems can react instantly instead of waiting for manual review later.
This is like giving football scouts a supercomputer assistant that has watched every match in the world and read every stats sheet, then pointing it at "find us the next star that fits exactly how West Ham plays."
This is a playbook from AWS for running your IT operations with a ‘smart autopilot.’ It explains how to use AI to watch logs, metrics, and alerts so it can spot problems early, suggest fixes, and sometimes even act automatically—before users notice something is broken.
Think of it as a “check engine” light on steroids for jets, ships, and vehicles: AI constantly watches sensor data and maintenance logs and warns commanders *before* something breaks, so they can fix it during downtime instead of in the middle of a mission.
Imagine your entire order-to-delivery process as a relay race where different specialists carry the baton: one checks inventory, another chooses the best supplier, another plans shipping, and another keeps the customer updated. This solution uses a team of AI “agents” on AWS to coordinate that whole relay automatically, so orders move from quote to delivery with minimal human intervention.
This is like giving your call center or helpdesk a smart ear that listens to what customers say (emails, chats, social posts) and instantly tells you if they’re happy, angry, or worried, using prebuilt AI from cloud providers.
Think of Azure AI Video Indexer as an AI librarian for all your videos. It automatically watches every video, recognizes people, objects, brands, spoken words, and emotions, and then turns that into searchable labels and timelines so your teams can instantly find the exact moments they need instead of scrubbing through hours of footage.
Imagine your entire IT environment—servers, networks, apps, cloud services—constantly watched by a smart assistant that never sleeps. It reads all the logs, alerts, tickets, and performance data, spots early warning signs, figures out what’s really important, suggests fixes, and in many cases can trigger automated responses before users even notice a problem.