Qlo

AI-native underwriting workstation for commercial MGAs and program administrators

Underwriting & Risk Startup Seed

Overview

Qlo is an AI-native underwriting platform for commercial insurance MGAs and program administrators, focused on P&C commercial lines. The platform automates the operational work around a submission, including clearance, document ingestion, data extraction, and rating, spanning the full cycle from first broker email through quote, bind, policy issuance, and renewal. Underwriters retain control of appetite, pricing, and terms decisions; Qlo's stated role is to remove the manual work that otherwise limits how much in-appetite business a team can process without adding headcount.

The platform is designed to run alongside a customer's existing policy administration system rather than replace it, so adoption can start with a single workflow, program, or line of business. Submissions, quotes, binds, policies, and renewals share one record rather than being tracked across separate tools, and configurable rating logic runs each customer's own pricing and appetite rules. Every data value and action is traceable back to its source document, providing an audit trail for underwriting decisions.

Qlo was founded by Ryan Hu and Liv Huang and is backed by Y Combinator (S26 batch). Distinguished Programs Executive Lines, an early customer, reports 3x primary quote throughput after adopting the platform. The company runs a Design Partner Program with commercial MGAs and program administrators, combining a tailored pilot period with a discounted multi-year contract ahead of production rollout.

Products & Services

Qlo Underwriting Workstation

An AI-driven workstation covering the full commercial-lines submission lifecycle, from intake through renewal, built to sit alongside a customer's existing policy administration system.

Key Features

Automated clearance, including hard and soft gates such as OFAC checks, before a submission proceeds
Document ingestion that extracts submission data (business type, layer, loss runs, missing items) from broker applications and supporting files
One shared record per risk across submission, quote, bind, policy, and renewal
Configurable rating logic that runs each program's own approved pricing and appetite rules
Traceability of every data value and action back to its source document

Target Users: Underwriting teams at commercial insurance MGAs and program administrators

At a Glance

Headquarters: New York, New York, United States
Funding: Seed

Category & Focus

Category: Underwriting & Risk
Subcategories: Automated Underwriting Submission Management Commercial Lines Underwriting
Insurance Verticals: P&C Commercial
Target Customers: MGAs/MGUs