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Stan founded Gradient AI as a product inside Milliman, a global insurance provider. As everyone knows, training AI requires data, and a lot of it. If you want to improve loss ratios for example, you need data on both insurer exposure and losses/claims made; data that is not easy to come by. 

However,  working inside Milliman gave him access to data that customers were providing to Milliman helping them develop these large AI models. 

But why insurance in the first place? 

Work-comp (insurance claims relating to injuries or death on duty) was the poorest performing subsegment with >100% loss ratios (i.e., claims are significantly larger than premiums). The problem was primarily that work-comp payouts happen over 5-10 (or more) years, with 10%+ medical bill inflation, it’s nearly impossible to accurately price worker compensation contracts today. 

Stan knew that he found PMF when  he  spoke with different prospective customers and they all voiced a clear need to identify bad claims early.

In 2020, the company spun out of Milliman. This allowed Gradient AI to grow faster, free from the internal competition and constraints of a large organisation.

Stan targeted small underserved businesses (2-10 employees), that had limited IT infra, and limited budgets, and would make their decision solely on ROI. 

Testament to how painful these issues were to their clients  prior  to Gradient’s  solution, all Gradient had to do was catch a few bad claims to save them hundreds of thousands of dollars, and the  gamble paid off. Gradient AI’s model successfully identified over 90% of high-risk claims within the first 30 days, a dramatic improvement over the client’s existing 15% identification rate. 

After spinning out from Milliman, Gradient AI required seed funding to get off the ground. At this stage, the main issue was surviving without the Milliman brand and data. However, AI was not as much of a household name as it is today and so most investors thought of it as an unproven, “voodoo” technology. 

However, investors remained drawn to Gradient AI’s ability to deliver real, measurable savings to its clients, leading them to secure their seed round from MassMutual Ventures.

Initially Stan wore many hats—serving as the CEO, CTO, and even part-time CFO. This approach was driven by necessity, as the company was bootstrapped, with Stan not taking a salary for the first three years and re-investing all fees back into the business. 

However, as the business scaled, it became evident that it could no longer hire rookies. They needed people who not only have done this before, but knew what the finished product looked like. Their hires turned from gritty, early-stage hires to seasoned executives.

Gradient AI leverages a typical multi-year SaaS model 

They deliver a positive ROI as they charge a portion of the savings generated for clients — this is a ROI-based structure with pricing calculated based on the direct-written premium (DWP) for underwriting solutions and the volume of claims for claims management solutions. 

Initially, sales were entirely founder-led, with Stan driving all sales efforts. However, as the company scaled, Gradient built out a dedicated sales team, bringing in experienced professionals who understood the intricacies of insurance. The company now employs a multi-channel GTM strategy that includes direct sales, partnerships, and strategic alliances.

Given the complex nature of the insurance industry, sales cycles can be long, often requiring several months of consultation and negotiation. However, contracts are typically high-value and long-term, ensuring a stable revenue base. Gradient’s value-based sales approach (i.e., clearly articulating the ROI and providing evidence of substantial savings) has been crucial in securing these contracts, even with the more conservative and risk-averse segments of the market.

Team Size: 10 employees

Focus: Establish PMF and validate the contributory data model.

Key Challenges: (i) Transitioning from a corporate structure to an independent startup. (ii) Securing initial clients and proving the value of AI in a traditionally conservative industry.

Key Achievement: Successfully demonstrated ROI for early clients, leading to the first major customer contract.

Team Size: 25 employees

Focus: Scale product offerings in the P&C insurance market and launch the health insurance vertical.

Key Challenges: (i) Developing new products while managing cash flow and maintaining momentum. (ii) Navigating the early stages of the COVID-19 pandemic, which impacted customer acquisition and product launches.

Key Achievement: Launched new business underwriting solutions in health insurance, driving rapid customer adoption.

Team Size: 50 employees

Focus: Accelerate sales and marketing efforts, expand customer base, and continue product innovation.

Key Challenges: (i) Scaling the sales and marketing teams to meet growing demand. (ii) Balancing rapid growth with the need to maintain product quality and customer satisfaction.

Key Achievement: Exceeded growth projections, with significant traction in both the P&C and health insurance markets.

Gradient AI closed a $56Mn Series C in July 2024. With the additional funding, Stan plans to:

If you are an investor or would like to work with Gradient AI, get in touch at [email protected].

Open job listings are also available at: https://job-boards.greenhouse.io/gradientai

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