Prediction markets are having a moment. Combined monthly trading volume on Kalshi and Polymarket grew from under $5 billion in September 2025 to about $24 billion in April 2026, according to CNBC. Founders, sportsbooks, exchanges and media companies are all asking the same question: how hard is it to build one?
This guide walks through how these platforms work, the product and technical decisions you need to make, and what the regulatory side looks like in 2026. It is written for founders and product leads, not lawyers, so treat the legal sections as a starting point for a conversation with your counsel.
What a prediction market actually is
A prediction market lets people buy and sell contracts on the outcome of a future event. Most use simple Yes/No contracts:
- A Yes share pays $1 if the event happens and $0 if it does not.
- A No share pays the opposite.
- One Yes share plus one No share is always worth exactly $1.
If a Yes share on "Will the Fed cut rates in December?" trades at 73 cents, the market is saying there is roughly a 73% chance it happens. Traders can buy, sell before the event settles to lock in a profit or cut a loss, or hold to settlement.
That last point is what separates a prediction market from a sportsbook. On a sportsbook you bet against the house at fixed odds. On a prediction market you trade against other users, prices move continuously, and the platform earns a fee on trades rather than profiting when users lose.
Step 1: Decide which kind of platform you are building
Before any technical choice, pick your model. It decides your tech stack, your licence and your audience.
| Model | Example | Money | Best for |
|---|---|---|---|
| Regulated exchange | Kalshi, Polymarket US | Fiat, fully collateralised | US or other licensed markets |
| On-chain market | Polymarket (international) | Stablecoins like USDC | Crypto-native audiences where permitted |
| Free-to-play | Points-based apps | Points, no cash value | Markets where real-money play is restricted, and brand engagement |
Many teams start free-to-play to build an audience and prove engagement, then add a real-money product in a market where they hold a licence.
Step 2: Choose how prices are made
This is the most important technical decision on the platform.
Central limit order book (CLOB)
Users place limit orders and the engine matches buyers with sellers by price, then by time. Kalshi and Polymarket both use order books. Polymarket's documentation describes a hybrid model: an operator matches orders off-chain, and trades settle on-chain from signed orders.
Order books give the fairest prices once you have active traders. The downside is thin liquidity in new or niche markets, where the spread can be wide or there may be no one on the other side at all.
Automated market maker (LMSR)
The logarithmic market scoring rule, designed by economist Robin Hanson, is a formula that always quotes a price. The platform acts as the counterparty and the price moves as people buy. It solves the empty-market problem, but the platform takes on risk, and large trades move the price more than they would on a deep order book.
What we recommend
If you expect real volume on a few big markets (major sports, crypto prices, economic data), start with an order book and seed liquidity with a market maker. If you plan to run hundreds of small markets, an AMM or a hybrid is easier to launch. Building the matching layer behind a clean interface means you can switch later without rewriting the apps.
Step 3: Design the architecture
A production prediction market has five core pieces.
- Matching engine. Runs in memory for speed and writes every event to a durable log so it can be replayed after a crash. It must never double-fill an order.
- Wallet and ledger. A double-entry ledger where every deposit, trade, fee and payout is two balanced entries. This is what makes your numbers reconcile and what auditors will look at first.
- Market service. Creating markets, setting rules, opening and closing trading, and storing the resolution source.
- Settlement. Resolving the outcome, either manually by an admin, from a trusted data feed or through an oracle, then paying winners. A dispute window before final payout protects you from bad data.
- Real-time layer. WebSockets that push prices, fills and balances to every user instantly.
Around those you need KYC and AML checks, geo-fencing, a risk console for your operations team, and the iOS, Android and web apps.
| Layer | Typical choices |
|---|---|
| Apps | React Native or Flutter, Next.js for web |
| Matching and core services | Go, Rust or Node.js |
| Data | PostgreSQL, Redis, Kafka or another event log |
| On-chain (if used) | Solidity contracts on Polygon or Base, USDC collateral |
| Infrastructure | AWS or GCP, Kubernetes, autoscaling |
The biggest mistake we see is treating the ledger as an afterthought. Get the money flows right first and build the screens on top.
Step 4: Plan for match-day traffic
Prediction markets are spiky. Traffic during the final overs of a cricket match or a Fed announcement can be many times your daily average. Plan for:
- Load testing with realistic spikes before launch, not after.
- Per-market circuit breakers that pause trading if prices move abnormally.
- Rate limits that stop bots from flooding the order book.
- Read replicas and caching so viewing prices never slows down placing orders.
Step 5: Build compliance in from the first sprint
Regulation is the part that decides whether you stay live. The picture in 2026 is moving fast.
- United States. Kalshi and Polymarket US operate as CFTC-regulated exchanges (Designated Contract Markets). In June 2026 the CFTC proposed new prediction market rules that would allow most sports contracts but ban contracts open to manipulation, such as individual player injuries. Several states dispute federal authority over sports contracts, so this is still being fought in the courts.
- United Kingdom. The Gambling Commission said in February 2026 that prediction markets on sport and politics would likely need a betting intermediary licence. Contracts on financial events fall under the FCA, which treats them as binary options that are banned for retail investors, although reports in September 2026 said the FCA was in talks about easing that ban.
- India. The Promotion and Regulation of Online Gaming Act, 2025 bans all online money games, their advertising and payments for them, with the rules in force from 1 May 2026. Real-money opinion trading is not an option there. Free-to-play prediction apps are.
Whatever the market, the same controls come up: identity and age verification, geo-fencing by country or state, deposit limits and self-exclusion, an audit trail of every order and payout, and clear rules for how each market resolves. These are much cheaper to build in at the start than to retrofit.
This section is a summary, not legal advice. Confirm your licensing route with a lawyer in each country you plan to operate in.
Step 6: Launch, then expand market by market
A sensible launch path looks like this:
- Weeks 1 to 2: Scope the market model, target countries and licence route. Design the trading flow.
- Weeks 3 to 8: Build the ledger, matching engine and settlement, then the apps and admin console.
- Weeks 8 to 10: Load test, security review, reconcile the ledger under stress, beta with real users.
- After launch: Add categories, automated resolution, referrals and market-maker tooling as volume grows.
That gets a focused MVP live in about 8 to 10 weeks. A full platform with native apps on both stores and automated resolution usually takes 14 to 20 weeks.
How WebAziz helps
We build prediction market and opinion trading platforms end to end: matching engine, ledger, KYC, settlement, admin console and native apps. For real-money builds we work with your licensing advisors from day one. For markets like India we build free-to-play versions that make money from sponsors, ads and subscriptions. You own all of the code.
See what we build on our prediction market app development page, or read our guide to what a prediction market app costs to build.
Frequently Asked Questions
Can I legally build an app like Kalshi or Polymarket?
You can build the software anywhere. Operating it with real money needs a licence in each country where users trade. In the US that means CFTC registration as an exchange or partnering with one, and in the UK it likely means a Gambling Commission licence for sports and politics markets.
Should I use an order book or an AMM?
An order book gives better prices once you have active traders and is what Kalshi and Polymarket use. An AMM such as LMSR always quotes a price, which helps when markets are new or niche. Many platforms start with an AMM or seeded liquidity and move to an order book as volume grows.
Do I need blockchain to build a prediction market?
No. Kalshi runs entirely off-chain. Blockchain is useful if you want stablecoin deposits, transparent on-chain settlement or a crypto-native audience, but it adds smart contract audits and more regulatory questions.
How long does it take to build a prediction market platform?
A focused MVP takes about 8 to 10 weeks. A full platform with native iOS and Android apps, automated resolution and market-maker tooling usually takes 14 to 20 weeks.
Can I launch a prediction market in India?
Not with real money. The Online Gaming Act 2025 bans online money games, including opinion trading. You can launch a free-to-play prediction app that uses points and earns from sponsors and ads.
Sources
- Prediction markets regulation proposal by CFTC eyed by White House, CNBC
- No injuries, no props: CFTC proposes prediction market rules, ESPN
- Some states want to regulate prediction markets. Should the feds let them?, CBS News
- Prices and the order book, Polymarket documentation
- Polymarket plans to re-enter US with acquisition of QCEX, The Block
- FCA weighs easing UK's financial prediction market ban, Gambling.com
- A New Era of Online Gaming Governance, PIB