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.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Helped EGPAF develop glAIser, an Azure AI-powered data mining assistant to surface insights.
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.
Staff wasted hours digging through six data silos. AI now scans 500k records in seconds, saving the team 50 hours daily.
Finance manually chased missing global travel receipts. Now, AI prefills transaction data and automatically flags spending anomalies.
Manual survey tagging kept staff from the field. Now, workers use Copilot to analyze donor feedback and build tracking apps in days.
Silos forced a 71-day wait for data. By unifying sources, 4,000 staff now access insights in hours and build models 50% faster.
Disparate tools slowed 320,000 employees. Unifying on Teams and Copilot connected the workforce and embedded AI into daily habits.
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.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Helped EGPAF develop glAIser, an Azure AI-powered data mining assistant to surface insights.
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.
Staff wasted hours digging through six data silos. AI now scans 500k records in seconds, saving the team 50 hours daily.
Finance manually chased missing global travel receipts. Now, AI prefills transaction data and automatically flags spending anomalies.
Manual survey tagging kept staff from the field. Now, workers use Copilot to analyze donor feedback and build tracking apps in days.
Silos forced a 71-day wait for data. By unifying sources, 4,000 staff now access insights in hours and build models 50% faster.
Disparate tools slowed 320,000 employees. Unifying on Teams and Copilot connected the workforce and embedded AI into daily habits.