Learning to Scale (and to Stop) in AI Local Tourism

Learning to Scale (and to Stop) in AI Local Tourism

Role
Role

Founder & CEO

Industry

Travel & Tourism

MY ROLE

Product Design

Fundraising & Negotiation

Hiring & Management

Board reporting

Business Growth

TEAM

Co-Founder & CTO

Co-Founder & CFO

2x Frontend Engineers

2x Backend Engineers

1x System Architect

2x Data Analysts

2x Account Managers

Videographer

Marketing Manager

Operations Manager

TL;DR

Jedo was a founder-led attempt to unlock local tourism through AI-assisted trip planning and booking. The market showed strong demand. Despite early traction and strong unit economics, market shifts limited growth. We chose to stop.

53,000

registered users

$100,000

profit at $0.73 CAC

+76%

Increase in monthly bookings

+43%

average spend per booking

Disclaimer: Confidential information has been omitted or obfuscated. This case reflects my own perspective and does not necessarily represent the views of Temper.

CONTEXT

Working in consulting meant more travel, and less time to discover the local cultures.

Lebanon has a whole lot to offer (and no, it doesn’t have a desert). Yet so many people find it very hard to plan their trip there.

~400,000

Weekly active local tourists market

80%

can't find excursions
that suit their tastes.

60%

see access to local attractions as main blocker

The goal was to create a solution that would streamline the discovery of local experiences, making it easier and quicker for travelers to find activities that matched their preferences.

Content (I also wish it was more visual)

DIRECTION

After an mvp with little traction, we realised Local AI Travel is a tough, and exciting nut to crack.

I coached the team on continuous discovery, and lean execution. By that, we learned that the problem wasn’t lack of demand. It was lack of facilitation and reach in a fragmented ecosystem:

Locals

valued spontaneity, yet spent long time deciding where to go

Merchants

aka Local Businesses, managed bookings on pen & paper

DMOs

aka Destination Management Organizations, acted as regulators, not connectors

Mapping of flows and architecture

OUR OFFER

For Tourists

Low-friction discovery to support fast, spontaneous trip decisions

For Merchants

Minimal operational overhead through simple booking flows

For DMOs

Real usage signals and analysis on behavioral data, tourist and destination research

For Authorities

Reports that enabled behavior and data-based strategies

Initial Mult-varaite tests we did (The middle won)

GROWTH
& Closure

We secured $100,000 and launched V2. It exceeded every expectation.

We did $12,000 profit within two months. And right after the second release, we hit:

53,000

Registered & Active Users

$100,000

Profit in 6 months

$0.73

CAC

Shortly after, he outbreak of war in Gaza and Southern Lebanon severely impacted the tourism industry, halting demand and scaling plans.

In response, a strategic partnership was formed with a startup studio in Saudi Arabia. However, we had no runway, investment, and minimal on-the-ground work in KSA.

Based on these signals, we made the decision to stop.

LEARNINGS

Designing for uncertainty means knowing when to accelerate and when to stop.

The same signal-driven discipline that enabled learning and fast iteration, enabled both rapid growth and a timely exit.

This mindset continues to shape how I evaluate product bets today: prioritizing learning velocity, structural advantage, and judgment over momentum alone.

Final version before the sunset