READY-TO-DEPLOY AI AGENTS
Automate policy management with agentic AI
Process endorsements, renewals, and servicing tasks 10x faster with an AI employee that never drops a request or miskeys a policy number.
Your operations team wasn’t hired to rekey data…
Servicing backlogs are growing
Teams are overwhelmed by endorsement requests, renewal updates, cancellations, and reinstatements—all handled manually.
15–45 minutes of human effort per average servicing task
Manual entry = costly errors
One mistyped VIN or effective date can trigger downstream claims and compliance issues.
Policy errors cost carriers millions in leakage and corrections
Slow turnaround time
Slow service frustrates brokers, agents, and policyholders—hurting satisfaction and renewal rates.
Every delay increases churn risk
Use agentic AI to manage policies—instantly and accurately
This agent is pre-trained to run the entire authorization workflow. Deploy once on your systems, and it continuously processes incoming requests.
Process endorsements and changes automatically
Magical logs into your policy admin system, locates the correct policy, and makes updates based on structured inputs—faster than a human.
Automatically apply rating changes, update limits, and push notices to agents and policyholders.
Magical reads submission forms, broker emails, and scanned docs—and applies changes without human input.
Zero data storage. All PII processed locally with full activity logs.
Step 1: Book a demo
We’ll show you how Magical fits into your policy workflows—without changing your core system.
Measurable results for operations and servicing teams
90%+
Faster processing times
Cut turnaround from days to minutes—without adding staff.
Near-zero
Servicing errors
Ensure every change is applied correctly, every time.
70%
Reduction in back-office workload
Automate high-volume, low-complexity tasks with zero disruption.
5X
Better agent and customer satisfaction
Deliver faster service, fewer errors, and higher renewal rates.
Works across your existing healthcare systems
