We find deals.

Subscription-first model

Most flight deal sites earn money when you click through and book. That creates a quiet conflict of interest: the more you spend, the more they earn. FairFares doesn't work that way.

We are funded by subscriptions. That means our only incentive is to show you the best possible deal — not the most profitable one. Some booking links may carry an affiliate parameter, which means we occasionally earn a small commission if you complete a booking. This never influences which deals we surface or how they are ranked — the algorithm only cares about price.

Free forever. Plus from €2.92\/mo (yearly) or €4.99\/mo. Pro from €4.08\/mo (yearly) or €9.99\/mo. Cancel any time; you keep access until the end of your paid period. See full pricing →

AI for thinking. Code for doing.

FairFares is built by ARAI — one founder and a team of AI agents. But ARAI operates on a principle that most AI products ignore: AI is for the hard thinking. Not the repetitive doing.

When we design how to detect a deal — what counts as a baseline, how to score rarity, when to trust a price signal — that's where AI earns its place. It reasons, it considers edge cases, it designs the logic. But once that logic is designed, we convert it to deterministic code that runs the same way, every time, without touching an AI model.

Every day, FairFares checks thousands of routes, compares millions of price points, and scores every deal — all without a single AI call. It's straightforward math, running fast, on cheap compute. The AI already did its job: it wrote and validated the algorithm.

This matters beyond cost. AI inference has a real energy footprint. Running an LLM to evaluate whether a flight is cheap — for every route, every hour — would be wasteful by any measure. Deterministic execution uses a fraction of that energy. You get the quality of AI-designed logic, without the ongoing energy cost of AI-powered execution.

The honest bit

The founder of FairFares has spent years working in IT for large multinationals and government organisations. Power and cooling are not theoretical concerns in those environments — they are real, recurring budget and infrastructure challenges. He's seen firsthand how fast energy demand grows as systems scale, and how rarely that cost is visible to the people writing the software.

Alongside that IT career, he studied Nature and Environmental Sciences at university — not as a hobby, but as a second serious path. That background isn't decorative. It's why the energy cost of software feels personal rather than abstract, and why the tension between building technology and caring about the natural world is one he's been sitting with for a long time.

Running a flight deal site while caring about the environment is a contradiction. We're not going to paper over it. Flights emit CO₂. Datacenters consume power. AI models are energy-intensive. We know this better than most.

What we can do: design systems that are as efficient as possible, use AI deliberately rather than reflexively, contribute to carbon removal, and make it easier for you to travel consciously. When you book a deal you found here, consider adding a CO₂ offset — most airlines offer it at checkout, and independent certified providers exist for those who want to go further. We're not going to pretend that makes flying carbon-neutral. But doing something is better than doing nothing.

2% for the planet

FairFares participates in Stripe Climate — 2% of every payment we receive goes directly to carbon removal. Not offsets. Not tree planting. Actual, permanent removal: direct air capture, enhanced rock weathering, and ocean-based methods that lock CO₂ out of the atmosphere for centuries.

The projects are selected and vetted by Stripe's Frontier initiative — independent scientific assessment, not marketing. We don't pick the projects; we trust the process.

Flying has a real climate impact. We're not pretending otherwise. This is the least we can do: direct a slice of every subscription toward technology that takes the problem seriously.