Scout InsurTech Interview with Kay

Kay is an AI workforce for insurance operations. They seek to eliminate repetitive work in submissions, renewals and servicing, saving hundreds of hours for your agency and brokerage. Chris Luiz sat with CEO, Vishal Rohra, to learn more about how Kay is impacting the industry.

Who are your clients?

Kay is currently working with mid-market independent agencies and brokerages, typically between a $20M to $200M book. Firms like Johnson Insurance, Fidella and Weed Ross save hundreds of hours in submissions every month. The company is now starting to move further upmarket and engage with some of the largest brokerages in the industry.

What does your product do?

Kay automates data entry workflows across submissions and servicing. It started with quoting commercial lines and has grown to personal renewals, carrier downloads, generating ACORDs, COIs and Proposals. Agencies simply send an email requesting quotes—for example, a BoP policy across several carriers—and Kay’s AI coworker takes over. It either requests any missing information or directly logs into carrier portals, completes all the required fields, obtains quotes and returns them to the user via their preferred tools like email or AMS. The key differentiator is that Kay doesn’t require users to learn a new platform—it integrates directly into the systems they already use. This sidesteps the adoption challenges that often hinder tools like comparative raters.

How much capital have you raised?

The company recently announced a $3M round by Wing VC, South Park Commons, 101 Weston Labs and several angel investors.

Was the company born from within or outside the industry?

Kay was born outside the insurance industry. The founding team initially focused on horizontal machine learning tools, specifically retrieval-augmented generation (RAG) systems. As they explored verticals to apply their tech, they found that insurance offered both better economics and more meaningful operational pain points. While the company didn’t originate in insurance, the founder's family background in brokerage (though in a different industry) gave him an appreciation for the agency model.

What growth metrics have you accomplished over the last 12 months?

In the past three months alone, Kay has grown monthly ARR by over 100 percent each month. With the recent product launch, we’ve added 7-figures in new pipeline with 30+ demos every week.

Within your domain, what is the current challenge the industry is facing?

The biggest challenge is a combination of labor shortage and outdated technology. Around 400,000 roles are either disappearing or going unfilled, and a significant portion of agency and brokerage work—around 60 percent—is still manual and repetitive. Agents are spending hours entering the same data into multiple carrier portals because APIs are limited and carriers often resist being commoditized. Current automation tools like RPA haven’t kept up, and the systems used today have only barely evolved from piles of paperwork to digital forms.

How does Kay take a unique approach to providing value?

Kay’s approach replaces both rigid RPA systems and outsourced virtual assistants by introducing AI coworkers that can actually reason. Unlike legacy tools that break with every change in workflow or portal, Kay adapts quickly—sometimes in hours. It enables far more flexibility and unlocks workflows that are otherwise too dynamic for rule-based bots. The user experience is seamless, since everything operates through existing channels like email or CRM. It’s scalable, requires no retraining and delivers faster results without friction.

What inspired the team to start this company?

The journey was not a straight line, but looking back, the founder sees clear inspiration rooted in his family’s brokerage background. Even though the business model was in a different space, the idea of serving brokers—people growing relationship-driven businesses within their communities—resonated deeply. The founder left a high-paying, machine-learning job to build something inspiring, and the goal remains to help others free up their time from uninspiring, repetitive work.

Can you share any goals for the next 12 months?

The primary focus is now on scale. After refining the product with early partners, the team is pushing to bring Kay to as many brokers and agencies as possible. Beyond expanding quoting automation, there’s also a strong emphasis on broadening the product’s ability to handle other workflows in submissions and servicing. From a tech standpoint, Kay will continue investing in making its AI even more adaptable to diverse insurance processes.

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