Engineers spent months pulling reports from siloed data. Now, an AI assistant lets clinicians instantly flag high-risk patients via chat.
A US-based healthcare nonprofit operating in 12 countries, managing billions of data points across disparate electronic health systems for over 18 million patients.
Program data was heavily siloed, causing significant delays in tracking critical measurements like mother-to-child transmission rates. Data engineers...
“Microsoft is helping us get to the next stage to reach our mission. This technology improves the efficiency and effectiveness of our solutions to maximize our data for better programming and higher quality care. This is a new era of up-to-date technology and expertise.”
Global nonprofit dedicated to preventing pediatric HIV and eliminating AIDS.
Helped EGPAF develop glAIser, an Azure AI-powered data mining assistant to surface insights.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Elizabeth Glaser Pediatric AIDS Foundation's Healthcare data analysis is part of this use case:
Related implementations across industries and use cases
Simple questions demanded 45 minutes of SQL. An AI assistant now answers 70% of internal analytics, freeing the team from routine queries.
Organizing tens of thousands of compliance documents bottlenecked audits. Now, AI structures files and drafts summaries for expert review.
Doctors spent 3 hours nightly reviewing complex records. Claude now synthesizes 300-page referrals into instant patient histories.
Simple questions demanded 45 minutes of SQL. An AI assistant now answers 70% of internal analytics, freeing the team from routine queries.
Complex queries bottlenecked access to insights. Agents now translate plain language into expert dashboards and root cause analysis.
Drafting grant proposals took hours, limiting new outreach. Now, AI generates tailored drafts so staff can focus on the narrative.
Manual grading bottlenecked 60-student classes. Claude now evaluates handwritten photos and generates personalized, bilingual feedback.
With 99% of records missing metadata, teams sifted unlabeled databases. Now, AI generates column descriptions for data experts to verify.
Manual document summaries bottlenecked experienced staff. Now, AI drafts preliminary risk assessments, freeing teams for complex advisory.
Engineers spent months pulling reports from siloed data. Now, an AI assistant lets clinicians instantly flag high-risk patients via chat.
A US-based healthcare nonprofit operating in 12 countries, managing billions of data points across disparate electronic health systems for over 18 million patients.
Program data was heavily siloed, causing significant delays in tracking critical measurements like mother-to-child transmission rates. Data engineers...
“Microsoft is helping us get to the next stage to reach our mission. This technology improves the efficiency and effectiveness of our solutions to maximize our data for better programming and higher quality care. This is a new era of up-to-date technology and expertise.”
Global nonprofit dedicated to preventing pediatric HIV and eliminating AIDS.
Helped EGPAF develop glAIser, an Azure AI-powered data mining assistant to surface insights.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Elizabeth Glaser Pediatric AIDS Foundation's Healthcare data analysis is part of this use case:
Related implementations across industries and use cases
Simple questions demanded 45 minutes of SQL. An AI assistant now answers 70% of internal analytics, freeing the team from routine queries.
Organizing tens of thousands of compliance documents bottlenecked audits. Now, AI structures files and drafts summaries for expert review.
Doctors spent 3 hours nightly reviewing complex records. Claude now synthesizes 300-page referrals into instant patient histories.
Simple questions demanded 45 minutes of SQL. An AI assistant now answers 70% of internal analytics, freeing the team from routine queries.
Complex queries bottlenecked access to insights. Agents now translate plain language into expert dashboards and root cause analysis.
Drafting grant proposals took hours, limiting new outreach. Now, AI generates tailored drafts so staff can focus on the narrative.
Manual grading bottlenecked 60-student classes. Claude now evaluates handwritten photos and generates personalized, bilingual feedback.
With 99% of records missing metadata, teams sifted unlabeled databases. Now, AI generates column descriptions for data experts to verify.
Manual document summaries bottlenecked experienced staff. Now, AI drafts preliminary risk assessments, freeing teams for complex advisory.