Ticket Resale Market Without Scalping

Inspiration

It started with a napkin and a bad memory. One of our team members spent months trying to get tickets to a sold-out reunion show, only to watch them vanish in under two minutes to bots, then reappear on resale sites minutes later at 4–5x face value. We'd all had some version of this experience — refreshing a checkout page at exactly 10:00:00 AM, losing a "queue" to a script, and eventually giving up or paying the markup out of desperation.

The more we dug into it, the more we realized the problem wasn't resale itself — reselling a ticket you can no longer use is a legitimate, useful thing. The problem was unregulated, anonymous, bulk resale that let bots and brokers extract value that should have gone to fans, artists, and venues. We wanted to build a market that made scalping structurally unprofitable instead of just morally frowned upon.

What it does

Fair Line is a ticket marketplace with a few core mechanics baked directly into the platform, not left to policy or trust:

-Verified, capped identity. One verified account per person, with hard limits on how many tickets they can purchase or list per event — no bulk-buying bot armies.

-Lottery-based access for high-demand drops. Instead of first-come-first-served (which rewards bots and fast connections), high-demand events open a randomized entry window. Everyone who enters within the window has an equal shot.

-Royalties on every resale. Artists and venues earn a small percentage on every legitimate resale, which flips their incentives — instead of fighting resale, they're motivated to push fans toward the platform that protects it.

How we built it

We split the project into three layers:

-Marketplace core — a transaction engine enforcing price ceilings and per-user purchase limits at the database and API level, so the rules couldn't be bypassed client-side.

-Identity & anti-bot layer — verification checks plus rate-limiting and behavioral heuristics to catch bulk-purchase patterns before they hit checkout.

-Lottery/allocation system — a randomized queueing mechanism for high-demand drops, replacing the traditional "race to click" model with a fair, time-boxed entry window and randomized selection.

We used a fairly standard modern web stack for speed (a relational database for transactional integrity, an API layer to enforce business rules server-side, and a frontend for the marketplace and lottery UI), prioritizing correctness of the pricing/allocation logic over polish, given the time we had.

Challenges we ran into:

Designing a lottery that actually felt fair. Our first version used a simple random number generator per user, but we realized we needed to guard against people creating multiple identities to get multiple lottery entries — which pushed us back into the identity verification problem. Enforcing price ceilings without killing legitimate resale. Set the cap too low, and people can't recoup even reasonable costs (fees, unavoidable price differences); set it too high, and you've just built a slower scalping platform. We iterated on the ceiling formula several times. Balancing incentives for venues. Venues often profit from partnerships with resale brokers today, so we had to think through why a venue would want lower resale prices — the royalty mechanism was our answer, but modeling it convincingly in a short timeframe was hard. Time constraints. Building verification, pricing enforcement, and a lottery system in a hackathon window meant we had to be ruthless about scoping our MVP

Accomplishments that we're proud of

A working end-to-end flow: verified signup → capped ticket purchase → lottery entry for a simulated high-demand event → capped resale listing. A price-ceiling enforcement mechanism that can't be bypassed from the client side. A pitch that resonated — when we demoed the lottery system replacing "fastest click wins," it visibly changed how people thought about ticket fairness.

What we learned

Scalping isn't really a technology problem, it's an incentive design problem. The tech is only useful once the incentives are aligned so that nobody profits from working around it. Small formula choices (like the exact resale cap percentage) have outsized effects on whether a system feels fair or feels broken — this took a lot of back-and-forth testing with sample data. Getting stakeholders (venues, artists) aligned matters as much as the tech itself; a fairer system only works if the people with market power have a reason to adopt it.

What's next for Fair Line

Real payment and identity verification integrations to move beyond our simulated verification layer. Dynamic royalty structures so artists can configure their own resale terms. Partnerships with small/mid-size venues to pilot the platform on real, live events instead of simulated ones. Fraud detection improvements to catch more sophisticated bot behavior beyond simple rate-limiting.