TL;DR: Qlo uses AI agents to run commercial underwriting operations from submission to renewal. We rebuilt the underlying system so agents can operate across the entire workflow, not sit beside another legacy system. One enterprise client signed a two-year contract, went live in May, and has since tripled weekly primary quote throughput. The end state is autonomous underwriting that follows each company’s underwriting judgment and stays within the carrier’s appetite.

Today, we’re launching the Qlo Inbox Agent.

https://youtu.be/aICb20uhqhU

The Problem

More than $110B in commercial insurance premium flows through U.S. MGAs every year. Much of the work still begins with an email from a broker.

Commercial underwriters can spend up to 80% of their day in the inbox, chasing missing applications, loss runs, and other submission documents. Even a submission with roughly $50K in annual premium can take 48 hours to turn into a quote.

Once the information arrives, teams still need to prepare the data, run the rater, and assemble the right endorsements and quote variants.

When volume grows, teams add headcount. But underwriting judgment is hard to train and keep consistent. Costs rise, good submissions remain untouched, and inconsistent decisions can hurt loss ratios.

More premium left on the table, now with more people on payroll.

What We Built

Qlo runs the commercial underwriting workflow from submission to renewal. Specialized agents handle each operational step, while supervisor agents coordinate the work and communicate with the underwriter.

The Inbox Agent is one of those supervisors. An underwriter can message it from a phone like a teammate. It understands the instruction, calls the right subagents, and completes the work inside Qlo.

The underwriter makes the call. The agents make it happen.

One of those subagents is the Rater Converter we launched on Bookface. It turns an existing rating spreadsheet into a validated digital worksheet the rest of the workflow can use.

This is what agent-compatible means to us: agents understand the workflow, have the right context, and can act across the system. Today, they execute the underwriter’s decisions. The end state is autonomous underwriting within each company’s judgment, appetite, and controls.

The party has begun. Let the agents dance on top of Qlo.

Guidewire and Vertafore helped define the last era of commercial insurance software. We’re building Qlo to define the next one.

Why Us

Before Qlo, Ryan spent 2.5 years building a commercial insurance marketplace and saw carrier-side systems up close. The company received acquisition terms from a public insurance company, and two founders who were customers there are now advisors to Qlo.

Liv previously led backend at a Taiwanese baby-monitor company generating roughly $15M in annual revenue. Ryan and Liv had already built together before starting Qlo.

We build alongside experienced underwriters who want to help define how commercial insurance will operate in the AI era.

Our Ask

We’re looking for:

• Introductions to commercial MGAs and program administrators, especially submission-heavy programs with complex rating files or underwriting teams hitting the limits of their current systems.
• Introductions to investors who understand commercial insurance and see the same path toward autonomous underwriting.
• Insurance operators with strong opinions about the future of underwriting. Even if you’re not looking for a new system, we’d still like to learn how your business works.

If you run an MGA or program, want to build with us, or see the same future as an investor, email us at founders@getqlo.com.

Commercial insurance moves slowly because distribution beats architecture.

But distribution eventually stops scaling when the architecture underneath it no longer works.

The system that solves the real problem will be adopted. Time will tell.

We’ll keep building.