TeamOut
The Airbnb for team retreats
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Garry Tan

TeamOut AI - The AI that plans your events

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Y Combinator
•
TeamOut is the first AI copilot for planning team offsites and corporate events. Instantly get tailored property recommendations, flight cost estimates, and exclusive hotel deals that save you up to 40 percent. No waiting, no planners, just smarter planning in minutes. Whether you are organizing a company retreat or a team gathering, TeamOut helps you go from idea to booked faster and easier than ever before. Perfect for remote teams and fast-moving startups.

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Amber Wang

@garrytan @vincalbouy Upvoted, love the idea of an AI copilot for team offsites! I can see how much time this is gonna save for the administrative and HR team, and I just love how we can empower every annoying time-eating tasks with AI even with team bounding!

And from a PM's perspertive, I'm curious how you balance venue quality vs cost/budget constraints in your recommendations. Is it purely data-driven from past team reviews, or do you combine qualitative signals (like team size, event style, and desired vibe) into your model?

Curious Kitty
When someone is already using a traditional stack (travel booking, spreadsheets, an event tool, or a venue-sourcing network), what’s the exact switching moment? What do they replace first, what do they keep, and what proof do they need to trust your recommendations and cost estimates?
Vincent Albouy
Maker

@curiouskitty those are interesting questions.

1. When do teams switch?
Most teams come to TeamOut when the “stack sprawl” starts to hurt: too many tabs, unclear budgets, slow venue replies, and no easy way to sanity-check options. At that point, they don’t want to restart, they want clarity.


2. What gets replaced first vs. kept?
TeamOut usually replaces the thinking layer first:

  • destination exploration

  • venue shortlisting

  • budget modeling & scenario testing

Teams often keep their existing tools (travel booking, expense, calendars) initially. We already integrate with tools like Navan, Brex, and spreadsheets, and we’re expanding integrations so TeamOut can sit on top of what teams already use, not fight it.

If planning is already underway, that’s not a blocker. LLMs are very good at ingesting context quickly: existing venue conversations, constraints, budgets, and preferences can be brought into TeamOut and continued seamlessly.

3. When do teams go all-in?
For new events, many teams go 100% TeamOut from day one. Planning is cyclical, and starting fresh without legacy tools is often the easiest path you provide context and dates, and we handle the rest in one place.

4. How do we earn trust (recommendations + costs)?
Two things:

  • Recommendations only come from venues we know well — places where we’ve organized real events, backed by human reviews and operational history.

  • Cost estimates are grounded in thousands of real historical quotes. And the final proof is simple: one click to request an actual quote. It’s fast, free, and removes any guesswork.

In short: teams don’t switch because they’re forced to they switch because TeamOut removes friction early, earns trust through real data, and lets them move faster with confidence.

thx for the support

An Ne
@curiouskitty This is a great question. In my experience, the switch usually doesn’t happen all at once it happens when the cost of coordination becomes more painful than the cost of change. People tend to keep their existing tools for booking and spreadsheets at first, and replace the part that’s causing the most friction (usually aligning constraints and trade-offs). Trust comes less from “perfect estimates” and more from seeing how recommendations are reasoned through step by step.
Hugo Roussel

Proud to be part of the team that built this. Been a wild ride watching it come together, from early prototypes to what you see today. If you've ever planned a corporate offsite, you know the pain.

We're trying to fix that. Give it a shot 🙏

Matteo Tittarelli

Congrats on the launch team @vincalbouy @thomas_mazimann2 !

Vincent Albouy
Maker

@thomas_mazimann2  @matteo_titta Thank you for the support

Jean-Baptiste Coger

There are soooo many tasks that you always feel are completely non value added when planning an offsite yet super time consuming and mandatory (coordinating flights, food etc..)
Glad someone is giving a try at fixing this with AI!
Nice work les gars @vincalbouy @thomas_mazimann2

Jerem Febvre

team off-sites are one of those things everyone knows are valuable, yet planning them is always way more painful than it should be. For remote and fast-moving teams, this is exactly the kind of tool that turns a “we should do an offsite” idea into something that actually gets booked. Congrats on the launch 🙌

sofia ragona

Hey everyone 👋
I’m Sofia, part of the TeamOut team, working on Venue Partnerships & Business Development.
Super proud to be part of this launch. If you’ve ever planned a corporate event, you know how broken and time-consuming the process can be. We truly believe AI is the missing piece here, and we can’t wait to hear your feedback 🚀

Kumar Abhishek

What makes TeamOut meaningfully different from working with a human event planner or using tools like Google Sheets, travel sites, and Slack together?

Nuseir Yassin

Once a plan is generated, can teams flexibly iterate, negotiate or customize deeply before actually booking everything?

An Ne
@nuseir_yassin1 This tends to be a critical moment. Teams usually need a space to explore “what-ifs” before locking anything in adjusting constraints, swapping priorities, or stress-testing alternatives. The tools that work best treat the plan as a living draft rather than a final answer, so iteration feels collaborative instead of risky.
S.S. Rahman

It made me think how will it handle distributed or global teams like ours. How does the AI handle visa constraints, time zones and travel complexity without oversimplifying the plan?

An Ne
@syed_shayanur_rahman This is an important point. In real-world planning, constraints like visas, time zones, and travel fatigue can’t be treated as static rules. The systems that work best tend to model these as evolving constraints rather than filters so the plan adapts as trade-offs surface, instead of collapsing everything into a “simple” answer that breaks in practice.
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