Building the professional trust graph for an AI-first world
CEO & Co-Founder of Catchouse. Previously Chief Product Officer at Tinder, where I learned the hardest problems in consumer tech aren't about matching, it's about trust.
I'm passionate about helping professionals get the full benefit of AI, not get flattened by it. In high-stakes decisions, the human relationship isn't a bottleneck, it is the product. Great AI should extend expertise, not replace it.
At Catchouse, we're building the structured trust layer that powers how AI recommends professionals to the people who need them.
AI has rewritten how people search. It hasn't changed how they choose.
It isn't reviews, credentials or content. It's corroboration.
No single signal decides whether an AI assistant names a local professional. What predicts it is agreement: different kinds of sources pointing to the same person.
Why AI assistants name some local professionals and ignore others: what 3,209 cited pages have in common
Two channels decide whether you are found: the one that ranks pages, and the one that names people. They are won differently, and most professionals are only playing the first.
We Ran 271 Queries Against ChatGPT and Google's AI: The Two Recommended Almost Completely Different People
In an era where artificial intelligence is increasingly shaping how people discover service professionals, we decided to put two of the leading AI engines, ChatGPT and Google's AI, to the test. Runnin
Realness, Respect, Relevancy: What Tinder Taught Me About Building Trust Between Professionals and the People Who Need Them
In the summer of 2023, I took the stage at the Reuters Momentum Festival and shared a simple yet key insight: Tinder had three core problems to solve: realness, respect, and relevancy. These weren’t j
Building the Trust Graph: Supporting Professionals and Consumers Through AI
Catchouse is Building the Trust Layer for Service Professionals