Use Case

Sovereign Multi-Agent Underwriting System at Swiss Re

October 12, 2023
April 9, 2026
8 min read
40
min read
Data visualization and AI network
85%Reduction in manual data entry time
60–75%
faster underwriting decisions
3.2xIncrease in underwriting throughput
30–50%
improvement in risk accuracy
100%Sovereign data compliance maintained
Significant
reduction in manual workload

Underwriting complex reinsurance risks involves massive unstructured data volumes and tight deadlines. Swiss Re’s sovereign multi-agent system automates data extraction, risk assessment, and decision support while maintaining full control and compliance.

The Challenge of Complex Reinsurance Underwriting

Before implementing Singularity IO's agentic platform, underwriting teams spent up to 40% of their time manually extracting data from PDFs, emails, and legacy systems. This not only slowed down the quotation process but also introduced the risk of human error in critical risk assessment models.

Business Challenge
Underwriting complex reinsurance risks involves massive amounts of unstructured data, tight deadlines, and strict regulatory oversight, making the process slow and resource-intensive.
How Agentic AI Helps
Swiss Re implemented a sovereign multi-agent underwriting system that automates data extraction, risk assessment, and decision support while maintaining full control and compliance.
Detailed Automated Business Process
The system uses specialised agents for document intake, intelligent data extraction, risk modelling, and compliance verification. Agents collaborate through LangGraph orchestration, escalating only the most complex cases to human underwriters with clear explainability.
Potential Business Impact
Faster underwriting decisions, improved risk accuracy, and substantial operational efficiency gains while ensuring full regulatory compliance.
Key Takeaways

Implementation Stack

LangGraphLlama 3 (Self-Hosted)ExoscalePostgreSQLn8n

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Measurable Impact

How Singularity's sovereign agentic workflows transformed operations and delivered concrete ROI for this implementation.

85%
3.2x
$1.5M
99.9%
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