About Jeff

Jeff Kischuk is co-founder and CEO of Tripian, a B2B travel tech platform he has been building since 2016. Tripian connects travelers under management with experiences, activities, and personalized recommendations — turning fragmented POI data into something travel companies can actually transact on. What started as hand-curated "perfect days" from local experts in Paris grew into a constantly updating data infrastructure with millions of points of interest, now fed by APIs, partner content, and an always-on curation system called TriBot.

What we talked about

From curated Paris days to two million data points — How Tripian moved from manual expert curation to automated ingestion, commercial partnerships, and real-time updates — including how COVID forced sharper data on opening hours, closures, and pickup options.

Why agentic AI changes the supply side — Not just another trend: agents need API-first endpoints and structured data, and legacy travel infrastructure was not built for that.

The Netflix personalization trap — Why true travel personalization is harder than streaming — and what that means for anyone building recommendation engines in the industry.

Data beyond bookings — Overtourism, municipal planning, social signals from TikTok and Instagram, and uses for travel data that go well beyond where to eat tonight.

Humans still in the loop — Despite AI and self-service, human travel advisors are not disappearing — and Jeff found that surprising.

Micro-friction and the connected trip — Expanding beyond flights and hotels to the small pain points of travel — pharmacies, clinics, baggage storage — and building trusted networks to solve them.

Sharpest moments

On why travel personalization is not Netflix:

people only travel 2.1 times a year. So the data sets you're getting on how a person behaves when they travel is really limiting.

When Google offered deeper Gemini personalization through Gmail and Maps history:

I've always been good with that, but am I willing to let it go that much?

On the moment ChatGPT-style LLMs felt like an existential threat:

every like the first reaction people had to tripping that it was going to be our death knoll that all of a sudden all this data was available.

On what surprised him most about post-AI travel behavior:

the attention people are bringing back to the human element into travel and maintaining that human connection

On running a data company with a small team in 2026:

with a team of 10 is what we've been able to do. And we talked about this at our year at kickoff this year is because of AI and because of tech that we use and evolve is our effective team capabilities have tripled.

Key takeaways

• Tripian's moat is structured, tagged, commercial-grade travel data — not generic LLM knowledge — built API-first since before the current AI wave.
• Agentic AI creates demand for endpoints and protocols; legacy travel companies need a transition layer, not a rip-and-replace.
• Travel personalization is structurally limited by how rarely people travel and how little loyalty they show to platforms.
• Privacy boundaries matter: even data-forward founders hesitate when asked to hand over Gmail, Maps, and photos to an AI.
• The experience economy post-COVID is real — but human advisors, guides, and trusted voices remain central to how people book.
• Tripian's B2B-only bet from 2019 looks prescient: enhance partners' UX rather than compete for traveler attention.
• The next frontier is micro-friction during travel, solved through curated partner networks instead of generic search.