Aviator — A Crash Game.
Built to Scale. Engineered to Win.
A real-time multiplayer crash game handling 1,000,000 concurrent users — with a custom-designed house algorithm that delivers 5% net profitability and retains 50–65% of Gross Gaming Revenue.
What is Aviator?
Aviator is a real-time multiplayer crash game built for the Indian real money gaming market. Players place bets before a round starts, watch a multiplier climb in real time, and cash out before the crash — or lose it all. Every second counts. Every decision is live.
This wasn't a reskin of an existing engine. We designed the entire crash algorithm, the multiplayer sync layer, the betting logic, and the house edge model from scratch — targeting 5% net profitability with 50–65% GGR retention baked into the math, not tacked on as a policy.
The real problem wasn't the game. It was the math.
Crash games look simple on the surface. Under the hood, they're one of the hardest categories to build — because the business only survives if the algorithm is provably fair, psychologically engaging, and mathematically profitable. Most teams get one of the three right.
- Existing crash game clones used imported RNG engines with no custom house edge control
- No Indian platform could handle 1M+ concurrent users in a single real-time game session
- GGR leakage was rampant — most platforms retained less than 40% due to poor bet/cashout modeling
- Players didn't trust outcomes — provable fairness was absent, leading to high churn after losses
- Android-first India market had no polished, fast, low-latency crash game experience
- Custom crash algorithm with configurable house edge — designed for 5% net profitability target
- WebSocket-based multiplayer sync layer stress-tested for 1,000,000 simultaneous connections
- Bet and cashout modeling that retains 50–65% of GGR through payout curve calibration
- Provably fair round verification using server seed + client seed hash model
- React Native Expo app optimized for mid-range Android devices — sub-100ms UI response
Built to feel premium at every screen.
Every screen was designed with the end-user in mind — someone on the move, often distracted, who needs information fast and decisions to be obvious.
Six systems. One seamless game.
Every feature was built around one constraint: it has to work perfectly for 1,000,000 people at the same time. No exceptions.
Proprietary RNG-based crash engine with configurable house edge parameters. Designed for 5% net profitability with mathematically provable fairness — not borrowed, not reskinned.
WebSocket architecture purpose-built for 1,000,000 simultaneous players in a single game room. Sub-second state sync across all connected clients with no drift.
Bet sizing limits, auto-cashout logic, and payout curves calibrated to retain 50–65% of Gross Gaming Revenue. The math is the product.
Server seed + client seed + nonce hash model. Players can independently verify every round outcome. Builds trust — and keeps players coming back after a loss.
In-app wallet with UPI, card, and net banking deposits. Instant withdrawals with fraud detection and daily limit controls baked into the transaction layer.
Real-time round monitoring, GGR dashboard, player activity flags, withdrawal approval queue, and house edge reporting — built for operators who need full visibility.
The numbers.
Real data. No estimates, no projections.
Stack chosen for real-time scale.
Every technology decision was made against one benchmark: can it hold under 1,000,000 concurrent connections without degrading game state?
Architecture built around the math.
Most crash game infrastructure failures happen at two points: the RNG layer (fairness breaks down at scale) and the sync layer (game state diverges across clients). We engineered around both.
- Custom provably fair RNG using HMAC-SHA256 — server seed committed before round, revealed after crash
- Crash point formula: H = 100e^(r) / (1 - h), where h = house edge parameter (tunable per deployment)
- 5% house edge achieved through payout curve calibration, not arbitrary result manipulation
- GGR retention of 50–65% engineered via bet limit architecture and auto-cashout incentive design
- Socket.IO cluster with Redis adapter — horizontal scaling across N nodes, all sharing game state via pub/sub
- Single authoritative game loop running server-side; clients receive state diffs, never compute outcomes independently
- Round lifecycle (betting → flying → crash → settle) managed as a state machine — no race conditions on cashout
- Load tested to 1,000,000 simultaneous WebSocket connections with <80ms average event propagation latency
- Idempotent bet and cashout APIs — duplicate requests from network retries cannot double-credit or double-deduct
- Withdrawal risk scoring based on velocity, amount, and account age — high-risk transactions routed to manual review
- Wallet ledger implemented as append-only event log — every balance change is auditable and reversible
- Razorpay webhooks with signature verification — zero server-side trust on payment callbacks
What we solved that most teams walk away from.
Real money + real time + real scale creates problems that don't exist in any other category of app development.
- 01Designing a crash algorithm that is simultaneously provably fair AND profitable — most implementations sacrifice one for the other
- 02Maintaining sub-100ms game state sync across 1,000,000 concurrent WebSocket connections without state divergence
- 03Preventing cashout race conditions where two simultaneous requests at crash moment could both succeed
- 04Mid-round network drops causing players to miss their cashout window — a trust-destroying UX failure in real money games
- Separated fairness proof from profitability model — HMAC-SHA256 handles trust, payout curve handles margin. Independent systems, both intact.
- Redis pub/sub game state broadcast with single authoritative server loop — clients are dumb renderers, never sources of truth
- Atomic cashout transactions using Redis EVAL Lua scripts — single-threaded execution makes concurrent cashout physically impossible
- Auto-cashout stored server-side before round starts — if client disconnects, the server honors their cashout target independently
“Anyone can build a crash game UI. The hard part is designing the math so the house wins consistently without players feeling cheated — and building infrastructure that doesn't fall over when a million people are watching the same number climb at the same time. That's what we did here.”
This is a category where the technical decisions are business decisions. Let's talk about what you're building — we know this space.