Kalshi vs Polymarket: Which Prediction Market Model Is Better to Build?

Centralized Prediction Market Architecture

Kalshi runs on a centralized backend, so the platform itself controls how markets get created, matched, and settled. Market creation isn’t open to just anyone. Kalshi keeps that process operator-controlled to make sure markets meet listing and compliance standards before going live.
User management works on an account basis, much like a traditional trading platform, with a central order book and matching engine handling execution.

Supporting all this is a layered infrastructure: risk controls to manage exposure, a compliance layer for regulatory requirements, a settlement engine to finalize outcomes, real-time data feeds for pricing, and admin controls that let the operator run day-to-day operations.

Developer comparisons highlight this centralized setup, along with REST, FIX access, and WebSocket, plus a CLOB-based architecture, as some of the more defining traits of Kalshi’s model.

Why Businesses May Choose a Centralized Model

A centralized setup gives the operator greater control over how the platform runs.
For businesses, this can mean:

• More direct control over market creation and trading rules
• Centralized administration and user management
• Easier implementation of compliance workflows
• Faster changes to platform and market settings
• Greater control over liquidity and risk management
• A more structured approach to customer support and issue resolution

The trade-off is that the operator takes on more responsibility for the infrastructure, controls, compliance processes, and day-to-day operation of the market.

Decentralized Prediction Market Architecture

Polymarket is built on blockchain infrastructure rather than a centralized backend. Users interact with the platform via crypto wallets, whereas trades are executed via smart contracts rather than a centralized system. A CLOB still handles order matching, but settlement occurs on-chain, removing the need for a central party to hold funds or finalize outcomes.

Market resolution depends on an oracle, which reports the real-life outcome so the smart contract knows how to settle. Transactions run on stablecoins, keeping pricing simple while staying within a crypto-native setup. The overall design is non-custodial, meaning users retain control of their funds at all times rather than depositing them with the platform.

Because activity lives on blockchain networks, all market data, from trades to settlement, is publicly visible. This also opens the door to Web3 integrations, letting the platform connect with wallets, other protocols, and on-chain tools easily.

Why Businesses May Choose a Decentralized Model

A decentralized setup can make sense for businesses targeting crypto-native users or looking for more blockchain-based infrastructure. It can provide:

• Transparency, since transactions and settlement are visible on-chain
• Self-custody, letting users control their own funds without requiring the platform
• Blockchain-based settlement, which removes a central point of control over outcomes
• Global accessibility where permitted, without depending on traditional payment rails
• Composability, making it easier to integrate with other protocols and services
• Web3 integrations, connecting naturally with wallets and existing crypto infrastructure
• On-chain verification, giving users a way to confirm outcomes independently.

The trade-off is that businesses need to account for blockchain dependencies, wallet interactions, smart contracts, and the regulatory requirements that apply to their target markets.

Central Limit Order Book

A CLOB matches buy and sell orders based on price and time. Buyers submit bids, sellers submit asks, and the system matches them when the prices meet. This is a common structure in exchange-based trading, and both Kalshi and Polymarket use CLOB-based trading.

Market depth shows how many orders are available at different price levels. A deeper order book can handle larger trades with less impact on the market price, while a thinner book can move prices more quickly. This order flow also supports price discovery, as the available bids and asks help determine the current market price.

Market makers help keep the order book active by placing buy and sell orders. This can improve liquidity and reduce the bid-ask spread. Fast order matching also matters, particularly when trading activity is high or users are placing larger orders.

AMM vs CLOB for Prediction Markets

An AMM (automated market maker) uses a pricing formula and a liquidity pool instead of relying entirely on matching individual buy and sell orders. This can provide liquidity even when there are fewer active traders, making it useful for newer or less-established markets.

A CLOB, on the other hand, gives operators more direct control over order matching, pricing, and market depth. It can work particularly well where there is enough trading activity and market-maker participation.

For businesses, the choice depends on the market design and liquidity strategy:

A hybrid model can also combine CLOB trading with AMM-based liquidity, giving operators another option when designing prediction market software.

Why Liquidity Matters

Liquidity plays a vital role in the trading experience. The bid-ask spread is the difference between the top price a buyer is willing to pay and the bottom price a seller is willing to accept. It tends to narrow as more participants trade, making it cheaper to enter and exit positions. Market depth, the volume of orders sitting at different price levels, determines how much size the market can absorb before prices start moving.

Without enough depth, traders run into slippage, where the price shifts against them as their order fills, especially with larger orders that can move thin markets significantly. Liquidity also drives price discovery, since active buying and selling is what allows a market to settle on a price that actually reflects current sentiment. Market makers play a central role here, providing consistent buy and sell quotes that keep a market tradable even during quieter periods.

How Operators Can Build Liquidity

Liquidity needs to be planned as part of prediction market platform development rather than treated as a post-launch feature. Operators can use several approaches:

• Market-maker integrations, bringing in professional or automated liquidity providers to keep quotes active
• Liquidity incentives, such as rebates or rewards that encourage trading activity
• Initial liquidity, seeding a market with starting capital or orders so it isn’t launching empty
• Order-book management, actively monitoring and adjusting the book to avoid gaps or imbalances
• Market selection, choosing which markets to launch based on likely demand and trading interest
• Cross-market liquidity, allowing capital or activity to flow between related markets within the broader prediction market infrastructure, rather than staying siloed
• Real-time monitoring, tracking depth and spread continuously to catch liquidity issues before they affect trading.

How Kalshi-Style Settlement Works

In a centralized model, the exchange or operator manages the resolution process. A typical setup includes:

• Contract rules: Each market states what needs to happen for a contract to settle as a particular outcome.
• Defined outcome source: The market specifies which source or criteria will be used to confirm the result.
• Exchange-controlled resolution: The operator checks the result against the market rules and confirms the outcome.
• Settlement: Once the result is confirmed, contracts are settled based on the stated rules.
• Audit trail: Records of market activity and settlement decisions give operators a clear history to review if questions arise.

The exact process can vary depending on the market and its rules.

How Polymarket-Style Resolution Works

A blockchain-based model can use an oracle to connect the market with information about a real-world event. The process generally involves:

• Blockchain: Market activity and settlement can be recorded on-chain.
• Oracle: An oracle provides the information needed to determine the outcome.
• Proposed outcome: A result is submitted based on the market’s resolution rules.
• Dispute mechanism: If the proposed result is challenged, the applicable process allows the outcome to be disputed and reviewed.
• Final settlement: Once the result is finalized, the relevant contracts are settled according to the market rules.

Resolution mechanisms can differ between products and markets. So businesses should look at the specific rules and infrastructure rather than treating every blockchain-based market as identical.

Why Resolution Design Matters When Building a Prediction Market

A prediction market needs clear resolution rules before users start trading. Operators should know what source will determine the outcome, who or what confirms it, and what happens if the result is disputed.

These decisions also affect the platform’s prediction market architecture, smart contracts, settlement logic, compliance controls, and audit records. Hence, they should be defined early as part of the overall prediction market development process.

Kalshi-Style API Architecture

Kalshi’s API is built on its centralized trading system. Developers can use its APIs to access market data, manage orders, and connect external applications to the platform.

• REST: Used to request market information, manage orders, and access account-related data.
• WebSocket: Provides real-time updates for prices, trades, orders, and other market activity.
• Market data: Provides information such as available markets, prices, order books, and trading activity.
• Trading APIs: Allow applications to place, manage, and monitor orders.
• Authentication: Controls access to account and trading functions.
• Institutional connectivity: Institutional users can connect through dedicated interfaces such as FIX, depending on their access and requirements.

This gives developers a familiar setup when connecting external applications to a centralized prediction market platform.

Polymarket API Architecture

Polymarket combines its trading infrastructure with blockchain and Web3 components. Developers therefore work with both CLOB APIs and blockchain-based tools.

• Market data: Provides information on markets, prices, trades, and other activity.
• CLOB APIs: Handle order-related functions and connect applications to the central limit order book.
• WebSocket: Supports real-time updates for market and trading activity.
• Wallet interaction: Enables users to connect crypto wallets and interact with the platform.
• Blockchain/RPC: Provides access to blockchain data and allows applications to communicate with the underlying network.
• Smart contracts: Support on-chain transactions and other blockchain-based functions where applicable.

For businesses, understanding these differences is crucial to building the architecture and integrations required for a prediction market platform.

Centralized Compliance Controls

A centralized model gives the operator more direct control over compliance processes. Depending on the target market and applicable requirements, the platform can include:

• KYC: Verify user identity during registration or before specific activities.
• AML: Monitor activity and apply controls designed to identify potentially suspicious transactions.
• Geolocation: Restrict access based on the user’s location and applicable market rules.
• User limits: Set limits on trading activity, deposits, exposure, or other account functions.
  Market restrictions: Control which markets are available to specific users or jurisdictions.
• Audit logs: Keep records of account activity, transactions, configuration changes, and other important actions.
• Risk monitoring: Track unusual activity, trading patterns, exposure, and other risk indicators.

These controls can be managed through a central administration layer, giving operators more visibility over users, markets, and platform activity.

Decentralized Compliance Challenges

A blockchain-based model can require a different approach because users may interact through wallets rather than traditional platform accounts. Businesses may need to consider:

• Wallet-based access: Determine how users connect and how platform access is controlled.
• Jurisdiction controls: Apply geographic restrictions where required, even when transactions use blockchain infrastructure.
• Smart contracts: Consider how compliance requirements interact with code that can execute automatically.
• Identity layers: Connect identity or eligibility checks with wallet-based interactions where necessary.
• Transaction monitoring: Monitor on-chain activity and identify transactions that may require further review.
• Oracle governance: Define how outcome sources and resolution mechanisms are managed and controlled.

The specific controls will depend on the platform design, target jurisdictions, and applicable regulatory requirements.

Why Regulatory Design Should Come Before Development

Regulatory planning should happen before finalizing the technical architecture. The business needs to identify its target jurisdictions, user access rules, market types, payment methods, identity requirements, and reporting obligations first.

The technical model should follow the target jurisdiction and operating structure, not the other way around.

This decision can influence whether a business chooses a centralized, decentralized, or hybrid approach. It also affects the prediction market technology, user flows, KYC and AML integrations, market restrictions, wallet architecture, transaction monitoring, audit trails, and administrative controls. These requirements should be defined early when businesses build a prediction market platform, helping reduce major architectural changes later.

When Centralized Architecture Makes More Sense

A centralized model suits businesses that need greater control over users, markets, and operations. It supports:

• Fast trade execution
• Centralized market and settlement control
• KYC, AML, and compliance workflows
• Fiat payments and account-based access
• Liquidity and risk management

It can be a practical fit for regulated markets and exchange-style prediction market trading platforms.

When Decentralized Architecture Makes More Sense

A decentralized model suits businesses focused on blockchain infrastructure and crypto-native users. It supports:

• Blockchain-based settlement
• Wallet-based access and self-custody
• On-chain transparency and verification
• Web3 integrations and smart contracts
• More distributed infrastructure

Operators should pick the architecture early when building a custom prediction market platform, as it affects scalability, integrations, infrastructure, and expansion.

Target Market

Define the users, regions, event categories, and market types the platform will support. This helps decide user access, payments, market rules, and platform features.

Regulatory Model

Identify the jurisdictions and regulatory requirements that apply before choosing the technical architecture. KYC, AML, geolocation, user limits, and market restrictions must be incorporated into the platform from the start.

Trading Model

Decide whether the platform will rely on an order book, an automated market maker, or a combination of both. The choice affects order matching, pricing, liquidity, and the overall trading experience.

Liquidity Strategy

Plan how markets will maintain enough liquidity for users to trade efficiently. This may involve market makers, liquidity incentives, initial capital, or a combination of approaches.

Settlement Model

Determine how market outcomes will be verified and contracts settled. A centralized platform may manage settlement internally, while a blockchain-based model can use oracles and smart contracts.

Technology Stack

Choose the infrastructure based on the scalability needs, platform model, integrations, and security requirements. This can include APIs, databases, blockchain networks, wallets, smart contracts, and real-time data systems.

Budget and Development Timeline

Define the budget and expected launch timeline before selecting the development approach. Scope, integrations, trading infrastructure, compliance requirements, and customization impact prediction market development cost.

Custom vs Turnkey vs White Label

Choose between a custom build, turnkey solution, or white-label platform based on the required flexibility, ownership, customization, and launch speed. A prediction market development company can help assess these options based on your business and technical requirements.

Choose a Centralized Model If You Need:

• Centralized control
• Operator-managed markets
• Traditional payment rails
• Strong compliance workflows
• Centralized risk management
• Exchange-style operations

Choose a Decentralized Model If You Need:

• Blockchain settlement
• Self-custody
• On-chain transparency
• Web3 integrations
• Crypto-native users
• Distributed infrastructure

Choose a Hybrid Model If:

• You need centralized compliance with blockchain-based settlement.
• You want operator control over markets while supporting wallet-based access.
• You need both traditional and crypto payment options.
• You want to combine CLOB trading with blockchain infrastructure.
• You need flexibility to adapt the architecture to different markets or jurisdictions.

For many businesses, a hybrid approach can provide a middle ground between centralized control and blockchain functionality. The architecture can be designed around the specific operating model rather than forcing the business into a purely centralized or decentralized structure.

How does Kalshi compare with Polymarket?

Kalshi follows a centralized exchange model, with operator-managed markets, account-based access, order-book trading, and platform-controlled settlement. Polymarket uses a crypto-native model that combines CLOB trading with blockchain infrastructure, wallets, and on-blockchain settlements.

Is Kalshi centralized or decentralized?

Kalshi follows a centralized model. The platform manages market creation, user accounts, trading, compliance controls, and settlement through its own infrastructure. This gives operators a more direct way to manage markets, users, risk, and platform operations.

Is Polymarket centralized or decentralized?

Polymarket uses a blockchain-based, crypto-native model with wallet interaction and blockchain-based settlements. Its trading infrastructure also includes a CLOB. The exact architecture and features can change over time, so operators should evaluate the specific infrastructure and market they plan to build around.

Which is better, Kalshi or Polymarket?

There is no single answer. A centralized model may suit businesses that need stronger control over users, markets, compliance, and operations. A blockchain-based model may suit businesses focused on self-custody, on-chain settlement, and Web3 integrations. The target jurisdiction and operating model should guide the decision.

Can I build a prediction market like Kalshi or Polymarket?

Yes. Businesses can build a prediction market using a centralized, blockchain-based, or hybrid architecture. The build can include market creation, CLOB or AMM trading, liquidity management, resolution, settlement, user management, payments, compliance controls, APIs, and administrative tools. The exact scope depends on the operating model and target market.

What technology is used to build a prediction market platform?

A prediction market can use a combination of backend services, databases, APIs, real-time communication, matching engines, payment systems, and analytics. Blockchain-based platforms may also require a blockchain network, wallets, RPC infrastructure, smart contracts, and oracle services. The technology stack should follow the platform’s trading, settlement, and compliance requirements.

What is CLOB in a prediction market?

CLOB stands for Central Limit Order Book. It matches buy and sell orders based on price and time. For operators, a CLOB provides direct control over order matching and makes market depth, bids, asks, and spreads visible.

What is the difference between centralized and decentralized prediction markets?

A centralized market gives the operator greater control over accounts, markets, compliance, trading, and settlement. A decentralized model moves more functions onto blockchain infrastructure and can support wallets, self-custody, and blockchain settlement. The choice affects compliance, infrastructure, user experience, and operational control.

How are prediction markets resolved?

Markets are resolved according to predefined contract rules and an outcome source. A centralized platform may verify the result and settle contracts through its own systems, while a blockchain-based platform may use an oracle and smart-contract-based processes. Operators should define the outcome source, dispute process, and settlement rules before a market goes live.

How much does it cost to build a prediction market platform?

The cost depends on the architecture, trading engine, integrations, compliance requirements, blockchain components, customization, and development scope. A ready-made or turnkey solution generally requires less development than a fully custom platform.

What should I choose: AMM, CLOB, or hybrid?

A CLOB can suit markets with active trading and market-maker participation. An AMM can provide built-in liquidity through a pool and may be useful where order-book activity is limited. A hybrid model combines both approaches and can give operators more flexibility. The right choice depends on expected trading activity, liquidity strategy, market design, and platform architecture.