Claims throughput
High-volume claims still depend on adjusters assembling context from policy, billing, and channel systems by hand.
AEOS for Insurance
AEOS orchestrates agents across the claim and policy lifecycle, triage, adjudication, underwriting support, and servicing, with policy, evidence, and human checkpoints built in.
Underwriting capacity, claims handling, and customer experience are limited by manual reasoning on fragmented systems.
High-volume claims still depend on adjusters assembling context from policy, billing, and channel systems by hand.
The same fact pattern can yield different outcomes across regions and teams, without a governed workflow layer.
Supervisors expect evidence on every model and workflow change. Black-box automation does not pass review.
First notice of loss to first meaningful contact often measures in days when workflows could run in minutes.
One runtime for orchestration, automation, and governance, deployed inside the perimeter your regulator expects.
FNOL, triage, adjudication, and servicing on one policy-checked platform. Exceptions reach humans with reasoning attached.
Outputs trace to policy language, fact patterns, and source data, evidence for supervisors and internal audit.
Connect policy, claims, and billing systems. Agents work alongside your core stack, no rip-and-replace.
AEOS supports a continuous transformation journey, progressing one or more end-to-end workflows at a time toward connected, AI-driven operations.
Start with one high-impact end-to-end process in insurance, where agentic automation compounds without new control gaps.
AEOS runs inside your perimeter with policy, evidence, and human checkpoints built into the platform.
Prove value on one workflow, then connect the next. Progress toward the autonomous enterprise, workflow by workflow.
Illustrative patterns, not an exhaustive list.
First notice captured, classified, and routed across channels. Adjusters open cases with context and documents already attached.
Policy and coverage reasoning for high-volume lines. Exceptions route to humans with a decision draft and audit evidence.
Submission intake and exposure summarization grounded in your guidelines and loss history, not public-model assumptions.
Controls enforced by the platform itself, not bolted on after. Every call, decision, and output preserved for audit.