Three months after his second successful exit, Ryan Fink found himself breaking a promise. “I told my wife, I’m going to take a year off, kind of recoup from the grind of being a founder, and that lasted all of about, I think, three months,” he shared in a recent episode of Category Visionaries. But it wasn’t just entrepreneurial restlessness that drove him back into startup life – it was a personal experience that revealed a glaring gap in the construction industry.
From Personal Pain to Market Opportunity
After selling Stream, his remote collaboration platform, Ryan built his first home. The experience was eye-opening, but not in a good way. “Going through that home building process saw that it was not digital whatsoever. And at the end of the build, I was left with a physical binder with very little of the information on my home,” he recalls.
This experience collided with an unrealized vision from his previous company. At Stream, they had worked toward creating digital twins of homes through micro video calls and support interactions. Now, Ryan saw a different path to that same goal – one that started with the construction process itself.
The Audacious Challenge
Ryan approached his current co-founder with what he calls “a audacious challenge” – “How do you create a digital twin of the home so that the homeowner’s empowered with all this information without making anyone go out and capture it?” The answer emerged from a unique insight: all the information already exists, it’s just not being captured effectively.
“All the information on the home flows freely and exists throughout the build process. But it’s not captured organized in any meaningful way,” Ryan explains. “So at the end of the build, it’s lost out into the ether.”
A Novel Technical Approach
Drawing on his background in computer vision and machine learning, Ryan envisioned a different approach. Instead of requiring builders to change their workflows, what if AI could work quietly in the background, capturing and organizing information as it naturally flowed through the construction process?
The goal was ambitious: to have their AI “generate a true semantic understanding, both spatial information from the blueprint, and then a semantic understanding from all the inventory, like the lights, flooring, the countertop, all the way down to grout and paint color.”
Building for Real Problems
Before writing any code, the team interviewed over 25 builders to validate their approach. This research revealed an opportunity others had missed. While most construction software focused solely on builder pain points, Digs saw the value of addressing both builder and homeowner needs simultaneously.
This dual perspective led to remarkable results. Within their first year, they’ve onboarded over 5,000 homes across all 50 states and several Canadian provinces, achieving a stickiness ratio of 41.4% – nearly triple the “world-class” benchmark of 16%.
The Future of Home Information
Looking ahead, Ryan’s vision extends far beyond construction documentation. “In three to five years, we hope that every new home in the US is generating a digital twin for the homeowner,” he shares. He draws an interesting parallel: “We have things today like Carfax for your car, but there’s nothing like home facts for your home.”
But the true potential goes even further. Ryan envisions Digs becoming “the API of the home” where “brands that homeowners love, whether it’s a retail brand, furniture, et cetera, or products or services, can plug into the home and provide new experiences that we haven’t even imagined today.”
For the construction industry, this vision represents more than just digital transformation. It’s about creating a new standard for how homes are built, documented, and maintained. Just as Carfax transformed how we think about vehicle history, Digs is poised to revolutionize how we think about home information – not through disruption, but through intelligent enhancement of existing workflows.
This approach, combining deep industry understanding with cutting-edge technology, suggests a new model for modernizing traditional industries: one that respects existing processes while quietly transforming them from within.
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