READY-TO-DEPLOY AI AGENTS
Automate underwriting with agentic AI
Accelerate risk assessment, eliminate manual data gathering, and scale underwriting capacity with an AI employee that works 24/7.
Underwriters weren’t hired to do data entry…
Time wasted

Underwriters spend hours gathering info from PDFs, portals, and spreadsheets—leaving less time for actual risk analysis.
60–70% of underwriting time is spent on non-judgment work
Slow turnaround = lost deals

Manual workflows delay quotes and approvals, frustrating brokers and costing business.
Every extra day cuts win rates and hurts broker satisfaction
Data inconsistencies

Copy-paste errors and scattered data sources lead to oversights and inconsistent risk scoring.
Manual errors = unpredictable loss ratios
Let agentic AI do the repetitive work—so your underwriters can do theirs
This agent is pre-trained to run the entire authorization workflow. Deploy once on your systems, and it continuously processes incoming requests.
Automate data collection and extraction
Magical pulls structured and unstructured data from submissions, portals, and internal systems—instantly and accurately.
AI reads loss runs, applications, and third-party data sources to surface key risk signals and missing information for underwriter review.
Magical generates a clean, complete file for human review or downstream rating—no toggling between systems.
All data is processed locally with zero storage—perfect for regulated environments.


Step 1: Book a demo
See how Magical fits into your underwriting workflow—no need to change core platforms or rating engines.
Measurable results for underwriting and operations teams
10x
Faster quote turnaround
Respond to brokers in hours—not days.
70%
Reduction in manual prep work
Cut the copy-paste and streamline every submission.
6X
More accurate risk reviews
Standardized data prep means no missing fields or overlooked red flags.
500+
Hours reclaimed per month
Let underwriters focus on judgment, not paperwork.
Works across your existing healthcare systems



























