Thesis

Our core thesis was that Generative AI created a unique window of opportunity to modernize “old industries”. 

We believed that people who were historically resistant to technology could no longer ignore the shift, making them finally open to digital transformation.

We chose the construction world not out of personal passion, but due to deep familiarity; Two of the co-founders have close family ties to the contracting and architecture industries. This proximity gave us a “foot in the door” to explore how AI could tackle inefficiencies in a massive, traditional market.

Validation

We adopted a research-heavy approach, speaking with dozens of individuals across contractors and real estate developers in Israel and the U.S.

To reach high-quality contacts in the U.S., we directly messaged industry experts who appeared on podcasts or had a strong LinkedIn presence, referencing specific episodes or content to build immediate rapport.
Our validation process focused on “reasoning through” the pain points of different segments.

We quickly ruled out real estate developers because they are essentially “deal hunters” who lack the scale or repeated engagement to justify opening an app. We even discovered that their manual methods, like using a simple phone calculator to estimate project costs, were surprisingly accurate, leaving little room for a technological “value-add”. 

Shifting focus to contractors, we asked open-ended questions about their daily struggles without pushing a specific product idea, seeking to uncover genuine “hair-on-fire” problems. Ultimately, we decided to step away after realizing that the construction industry’s core challenges did not generate enough personal conviction for us to pursue.

Why it didn’t progress

1. Low Willingness to Pay: We found that most contractors typically spend very little, only hundreds or a few thousand dollars, on software annually.

2. Low Market Ceiling: Our analysis of the landscape (funding, acquisitions, IPOs) revealed a market cap. If the best-case scenario was a $50M acquisition (based on market statistics we’ve conducted), it did not justify our investment of time.

3. No Network Effects: Minimal interaction of people or data between companies made building a sticky or viral product challenging.

4. Founder-Market Fit: Two out of the three co-founders realized a lack of true passion for construction, compounded by the blunt, dismissive attitude of some industry veterans toward even basic technology.

Insights

1. Analyze Market Behavior Early: Before building, examine the “exit landscape.” Assess acquisitions, funding, headcount, time-to-exit, and growth ceilings to ensure the market can support your ambitions.

2. Scale is the Best Use-Case for Tech: Technology shines when there is high volume and repetition; one-off, high-stakes projects (like real estate deals) often don’t need complex software.

3. Uncover Real Pain: Extensive discovery calls in the early stage are a powerful way to disqualify ideas and uncover real pain points.

4. “Old World” Resistance is Real: Despite the buzz around AI, some legacy industries still view tech as a secondary concern compared to physical and bureaucratic hurdles.

5. Even a Calculator Can be a Competitor: If a prospect can solve their problem with simple tools (such as a phone calculator or a simple backup), your high-tech solution might face an uphill battle.

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