Submission Flow by Provectus

As described on AWS Marketplace.

Submission flow is an AI-powered underwriting intelligence platform built on AWS that helps commercial and specialty P&C insurers protect combined ratio at the point of intake through appetite-aware triage, autonomous submission clearance, and accelerated quote-to-bind workflows. Leveraging Amazon Bedrock, retrieval-augmented generation, and MCP-enabled integrations, the solution connects underwriting workbenches, broker submissions, exposure data, and institutional knowledge sources to deliver explainable, citation-backed risk evaluation and pricing support.

The platform orchestrates five specialist AI agents across submission intake, triage and clearance, risk evaluation, pricing support, and bind and renewal processes, enabling underwriters to focus on high-value judgment decisions instead of manual queue management. Built on a scalable AWS-native architecture, the solution incorporates a continuously refreshed three-tier underwriting knowledge base combining regulatory guidance, class and peril intelligence, and carrier-specific bound book and loss history. This approach improves underwriting efficiency, increases hit ratio and quote-to-bind speed, and establishes a governed framework for continuously evolving underwriting intelligence and portfolio management.

Highlighted by the publisher on AWS Marketplace.

Autonomous underwriting triage. Uses AI-powered specialist agents to triage, clear, and prioritize inbound broker submissions against carrier appetite, reducing submission backlog and accelerating quote-to-bind cycles.

Explainable underwriting intelligence. Leverages Amazon Bedrock and retrieval-augmented generation (RAG) to provide citation-backed risk evaluation, pricing support, and renewal decisioning with transparent reasoning and auditability.

Continuously tuned knowledge base. Combines regulatory guidance, class and peril intelligence, and institution-specific bound book and loss history through a three-tier underwriting knowledge base with continuous feedback-driven refresh loops.