AirGem: Entwickler baut KI-Copilot zum Vergleichen von Flugpreisen

Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle Submission 💸

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle

I'm a frequent traveler in Brazil, and keeping costs down is my top priority when comparing flights. But finding a cheap option is only part of the work: I also need to compare departure times, stops, dates, personal preferences, and calendar conflicts, which often means opening dozens of tabs:/

That frustration led me to build AirGem: an open-source, privacy-first flight-search copilot that turns a natural-language travel request into a small set of evaluated, explainable flight options.

Find cheap flights from GRU to POA from January 1, 2027, to January 8, 2027, with a maximum budget of 1500 BRL.

AirGem parses the request, searches current flight data, evaluates candidates, considers calendar conflicts, and explains the selected options. It also shows alternative flights and booking links when the provider returns enough information.

The product idea is a focused travel-planning assistant for frequent travelers, remote workers, and people who want help making a travel decision. These are the users I could imagine paying for a reliable, explainable itinerary shortlist.

Flight-search assistants already exist. Google, for example, has an AI-powered Flight Deals experience that interprets natural-language travel ideas and searches its own flight inventory. These products are convenient, but they also tend to keep the experience inside a particular vendor's ecosystem.

That creates a question I kept coming back to: what if the most useful context is my calendar, but I don't want to give a travel platform ongoing access to it?

AirGem takes a narrower and more portable approach. Instead of connecting directly to a primary calendar account, the user can upload an.ics export with one button and set a travel buffer. The calendar is used to rule out conflicts during the search, then discarded with the rest of the transient session data.

The creative part is not trying to build another general-purpose travel chatbot. Rather, I tried to combine four pieces:

That combination makes the assistant useful without requiring the user to trust one company with the entire travel-planning context. It also means the application can be self-hosted, the inference provider can be changed, and the calendar data can remain under the user's control.

Try the live demo: https://airgem.onrender.com

The demo asks users to provide their own SerpApi key. The key is sent over HTTPS, kept only in server memory for the transient session, never logged, and cleared after the session expires or the search completes. Optional calendars are handled in the same transient way.

A privacy-first flight-search copilot that finds flights around your real calendar.

AirGem turns a natural-language travel request into a small set of practical flight options. It keeps calendar data local, uses Gemma for semantic work and keeps search, validation, availability checks, and trade-off filtering deterministic.

AirGem is being built as a submission for the Hacktoberfest Open-Source AI Challenge: Week 2 — Side Hustle.

This challenge asks for a new project with open-weight or open-source AI that solves a real problem someone could plausibly pay for. With this, AirGem's target user is a frequent traveler, consultant, freelancer, or remote worker who wants to find an affordable trip without manually comparing flight times against work, classes, appointments, or family commitments.

AirGem uses Gemma through Ollama by default, with OpenRouter as an optional fallback. This keeps the model replaceable and makes…