AI, Risk, and Reinvention: How Relativity6 Turned Early AI Innovation into Insurance Industry Impact
Back in 2015, Alan Ringvald was an MIT grad student immersed in machine learning research and helping peers commercialize ideas through the Martin Trust Center for MIT Entrepreneurship. One spontaneous application to business school, a thesis on AI, and a strong hunch about the untapped power of enterprise data later, Relativity6 was born.
From Aviation to Underwriting: A Data-Driven Pivot
Relativity6’s first big break came from the aviation sector. But as the team refined its proprietary AI models, years before “large language models” became a buzzword, Ringvald and his co-founder Abraham Rodriguez spotted a bigger, more unexpected opportunity: property and casualty (P&C) insurance.
“Insurance is one of the oldest, most data-rich industries out there,” Ringvald said. “It touches everything, but it’s incredibly resistant to change. That made it a perfect fit for what we were building.”
Relativity6 is committed to solving a deeply entrenched problem in the property and casualty world: helping underwriters accurately price risk by knowing, really knowing, what a business does.
The deceptively simple question: What does this business do?
That question is harder than it sounds. There are nearly 20 million small businesses in the U.S., and many of them operate in the gray zones of classification.
“Is that company a roofer or a carpenter?” Ringvald said. “It matters a lot to an insurer. The risk profile is totally different.”
Business models also evolve. A landscaping company might expand into roofing. A nail salon might double as a laundromat. What’s on paper doesn’t always reflect reality. Carriers need to verify that a company is what it claims to be. That’s where Relativity6 shines.
Zero-Question Underwriting
Relativity6 calls its solution “zero-question underwriting.” With just a business name and address, the platform uses AI and proprietary data to deliver real-time answers to critical underwriting questions. What does this business actually do? How many people work there, three or thirty? Is it located near a floodplain, in a high-crime area, or more than 15 minutes from a fire station?
“We serve underwriters,” Ringvald said. “We put the answers they need right at their fingertips when they need them most. No surveys. No delays. Just fast, accurate, decision-ready data.”
Turning Internal AI into External Value
Relativity6 isn’t just building AI solutions for others. The company is using those same tools to reinvent how it operates.
“When we started, it took millions of dollars and years of work to build the technology,” Ringvald said. “Now, with what we know, we can do 10x more with 1/10 the resources. We’re applying AI internally to become faster, leaner, and more responsive.”
The result—tailored customer solutions in weeks, not years, and at scale
That’s where the company’s edge sharpens. Most businesses scale by standardizing and simplifying products and processes to serve more customers with fewer variables. Relativity6 flips the script. Its command of AI and machine learning allows it to scale without sacrificing specificity, delivering customized solutions efficiently and cost-effectively.
“With this new wave of AI, we’re doing things I couldn’t have imagined two years ago,” Ringvald said. “It’s like water. We don’t have to invent it; we just need to decide what container to pour it into.”
In short, Relativity6 shows what’s possible when a company doesn’t just use AI but understands it at the core and builds with it as a native capability, not just a bolt-on tool.
The Payoff of Patience and Persistence
Building trust in a traditional industry like insurance didn’t happen overnight. Relativity6 earned its place the hard way—by showing up, delivering results, and growing one relationship at a time. Today, the company stands with its customers at the crossroads of cutting-edge AI and traditional industry expertise.
“We’ve never had this many opportunities in front of us,” Ringvald said. “Now it’s about staying focused and doubling down on what we know works.”
