Fund launches needed 3-4 weeks of manual research each. Teams linked internal data, and strategic questions once skipped got asked.
A global financial services firm operating across retirement, benefits, and asset management, serving more than 71 million customers in over 80 markets.
Launching a new investment fund required weeks of manual research across competitive analysis, market opportunity, regulatory requirements, and...
“Our problem was not a lack of expertise. It was where that expertise was going.”
Financial services provider offering retirement plans, insurance, and asset management.
Cloud computing platform and on-demand infrastructure services.
Principal Financial Group's Fund research is part of this use case:
Related implementations across industries and use cases
Seven analysts manually wrote notes for 200 products. AI agents now digest fact sheets to draft compliant commentary instantly.
Manually parsing thousands of documents slowed analysts. Now, a custom AI research engine synthesizes traceable market insights in hours.
Customer due diligence took a week of cold outreach. Now, analysts query an AI expert transcript library to finish research in 1 day.
Staff manually combed 350K+ documents scattered across legacy SharePoint. Now, AI semantic search instantly retrieves exact answers.
Manual research bottlenecked migrations. AI now synthesizes 200k pages of technical docs to answer queries, freeing experts for strategy.
Quarterly compliance updates meant costly reshoots. Now scripts regenerate instantly — no cameras, no vendors, no delays.
2,000 engineers paid up to $10K/month each on AI coding tools. Self-hosted inference cut costs 90%, debugging became routine.
Appliance insights bottlenecked through Slack—hours or days, shaped by who you asked. Now product teams query in plain English.
Scaling AI access across a 100,000-employee workforce risked system overloads. An auto-scaling platform launched with zero downtime.
Fund launches needed 3-4 weeks of manual research each. Teams linked internal data, and strategic questions once skipped got asked.
A global financial services firm operating across retirement, benefits, and asset management, serving more than 71 million customers in over 80 markets.
Launching a new investment fund required weeks of manual research across competitive analysis, market opportunity, regulatory requirements, and...
“Our problem was not a lack of expertise. It was where that expertise was going.”
Financial services provider offering retirement plans, insurance, and asset management.
Cloud computing platform and on-demand infrastructure services.
Principal Financial Group's Fund research is part of this use case:
Related implementations across industries and use cases
Seven analysts manually wrote notes for 200 products. AI agents now digest fact sheets to draft compliant commentary instantly.
Manually parsing thousands of documents slowed analysts. Now, a custom AI research engine synthesizes traceable market insights in hours.
Customer due diligence took a week of cold outreach. Now, analysts query an AI expert transcript library to finish research in 1 day.
Staff manually combed 350K+ documents scattered across legacy SharePoint. Now, AI semantic search instantly retrieves exact answers.
Manual research bottlenecked migrations. AI now synthesizes 200k pages of technical docs to answer queries, freeing experts for strategy.
Quarterly compliance updates meant costly reshoots. Now scripts regenerate instantly — no cameras, no vendors, no delays.
2,000 engineers paid up to $10K/month each on AI coding tools. Self-hosted inference cut costs 90%, debugging became routine.
Appliance insights bottlenecked through Slack—hours or days, shaped by who you asked. Now product teams query in plain English.
Scaling AI access across a 100,000-employee workforce risked system overloads. An auto-scaling platform launched with zero downtime.