Independent wealth managers live and die by new high-net-worth clients, and prospecting for them is slow, manual work: building lists, guessing at who the decision maker is, and sending cold outreach that rarely lands. The research is where the time went, and the research is what nobody wanted to do.
AI sales intelligence that automated the top of that funnel. Nora pulled public signals to find companies matching an advisor's target profile, identified the right people inside them, and generated a personalized first email for each one. The advisor opened every conversation already knowing why this person was worth it.
I'm not an engineer. I recruited two, ran the build from user research through engineering handoff, and designed the outreach workflow myself. We shipped an MVP and put it in front of a wealth management firm.
The firm paid for the pilot. That was the moment it became a business rather than a project.
Then the harder call. Scaling the data layer meant web scraping at enterprise scale, and the regulatory and data-security exposure that came with it wasn't something I was willing to carry into bigger clients. I explored a pivot toward selling through banks, then made the decision to wind Nora down rather than build on a foundation I didn't trust.
Version 3 flips the input. Version 1 started from companies; version 3 starts from life events, the moments when someone actually needs an advisor, and uses licensed data instead of scraping. Five names a week, approved by a human, sent as the advisor, paid for by the meeting.