Launching a prediction market platform holds great promise, but it also comes with unique challenges and risks. Startups and iGaming operators venturing into this space — whether in the US, Latin America, South Africa, or beyond — must navigate regulatory hurdles, liquidity issues, technological demands, and user trust concerns.

This white paper outlines nine key pitfalls to avoid when launching a prediction market business, along with strategies to mitigate these risks. By understanding these pitfalls and addressing them upfront, operators can increase their odds of success and ensure a smooth launch. Importantly, we will also highlight how leveraging a custom-built prediction market solution (such as those provided by Vinfotech) can help avoid these pitfalls and deliver a robust, compliant, and engaging prediction market platform.

1. Neglecting Regulatory Compliance and Trust

Pitfall

A common mistake is treating a prediction market like a simple betting website without accounting for the complex legal and compliance framework. In reality, prediction markets often blur the line between gaming and financial trading, subjecting them to regulatory scrutiny. For example, in the U.S., platforms like Kalshi operate under CFTC oversight, whereas others (like some crypto-based markets) do not. If you launch without proper licensing or compliance measures, you risk legal shutdowns and loss of user confidence.

Mitigation

Design for integrity from day one. Build your platform with compliance and transparency features at its core. This includes robust KYC/AML processes, geo-fencing to block prohibited jurisdictions, and audit logs for all transactions.

Establish clear market rules and publish resolution criteria in advance. Using independent oracles and data sources for outcome verification, setting position limits, and implementing circuit breakers are all best practices to maintain fairness. Ensuring these measures not only keeps you within legal boundaries but also builds user trust.

Vinfotech’s approach, for instance, emphasizes “Compliance & trust: KYC/AML hooks, geo-fencing, responsible gaming, independent oracles, and auditable settlement flows.” A platform built with such features will reassure both regulators and users that the markets are fair and well-supervised. In summary, do not launch until you have the necessary licenses or legal clearance for each target region and a compliance-ready platform – it’s the foundation for long-term viability.

Vinfotech’s Strategic Advantage: This is where Vinfotech’s architecture offers a decisive edge. Unlike rigid white-label providers that force all clients into a single compliance workflow, Vinfotech provides custom-built solutions with full source code ownership. This allows operators to implement granular, jurisdiction-specific logic.

# Dynamic Geo-Fencing: A user in New York might see a Free-to-Play version of the site (due to the ORACLE Act restrictions), while a user in Wyoming sees a Sweepstakes version, and a user in the UK sees a regulated betting version.

# Module Switching: Vinfotech’s platform allows for the integration of distinct modules for KYC, payment processing, and wallet management. If a payment processor bans sweepstakes transactions in a specific state, the operator can swap in a new provider or switch that state to a crypto-only or F2P model without halting operations globally.

# Audit Trails: With regulators shifting focus to "pipes and code" and operational resilience , Vinfotech’s robust backoffice logging ensures that every trade, dispute resolution, and geo-check is recorded and auditable, a critical requirement for surviving regulatory scrutiny.

2. Underestimating Liquidity Requirements

Pitfall

Another major risk is launching without a plan for market liquidity. A prediction market is only as good as its ability to match traders on opposing outcomes. In the early stage, you may encounter the dreaded “no counterparty” problem: when users click Yes or No and see “no counterparty available,” it hurts confidence and kills engagement.

This typically happens when most users bet on one side of an outcome and there aren’t enough users (or funds) on the other side to fill those orders. The result is unfilled bets, wildly fluctuating odds, and stale prices – a poor user experience that deters further participation. Many new operators underestimate how critical liquidity is; without active counterparties or pricing mechanisms, your market can stall from day one.

Mitigation

Implement a liquidity strategy from the outset. One proven approach is integrating an Automated Market Maker (AMM) into your platform. An AMM continuously provides quotes on both sides of a market based on a formula, ensuring that trades can clear even when user volume is low.

For instance, Vinfotech developed an in-house AMM so that “prices can move even when early volume is low,” configuring it to match the operator’s risk tolerance (setting initial liquidity depth, controlling price sensitivity to large trades, and managing spread/slippage). This means the system itself helps fill the gap until organic user liquidity builds up.

In addition to AMM integration, consider other liquidity boosters: limited price-range orders to concentrate matching, and early-bet incentives to encourage the first wave of bets. These techniques can prevent markets from feeling empty. In short, don’t assume users will come and provide liquidity organically – actively plan for it. By using tools like AMMs and structured incentives, you ensure that your prediction market offers a lively trading experience from the start, rather than a barren order book.

Vinfotech’s Liquidity Solutions: Vinfotech’s platform is designed to tackle the liquidity challenge through a multi-layered approach:

1. Configurable Market Making Engines: The platform supports both order-book matching (for mature, liquid markets) and dynamic AMM integration (for long-tail, niche markets). This allows operators to set "tick sizes," spreads, and fair-fill rules that protect the market integrity.

2. Bot Integration Capabilities: In the early stages, "synthetic liquidity" is often necessary. Vinfotech’s custom solutions allow for the integration of proprietary trading bots or third-party market makers who can seed the order books, ensuring that early users always see a tight spread.

3. Liquidity Mining & Incentives: Borrowing from DeFi, the platform can be configured to reward users who place limit orders (makers) rather than market orders (takers). By sharing a portion of trading fees or offering platform currency to makers, the operator crowdsources liquidity. Vinfotech’s flexible backend allows for the design of these complex incentive structures.

4. Risk Management Dashboards: To protect against the "toxic flow" that drains AMMs, Vinfotech provides granular risk limits, throttles, and circuit breakers. If a market moves too violently, the system can auto-pause trading, allowing the operator to assess if an external event has occurred, preventing the AMM from being arb'd to death.

3. Using Inflexible or Off-the-Shelf Technology Instead of Custom Solutions

Pitfall

In the rush to launch, some founders gravitate toward generic or off-the-shelf platforms (so-called “clone scripts”) to save time. The pitfall here is underestimating the complexity of a full-featured prediction market.

A simple script or white-label clone might handle basic betting, but it often crumbles under real-world demands – failing under heavy load, lacking robust security, or missing critical features for market operations. As one industry guide notes, “many teams approach this space with a ‘clone script’ mindset and underestimate the hard parts”.

Key functionalities like real-time price updates, order matching, dynamic odds calculation, secure wallet/ledger management, and audit trails for settlements are not trivial to implement. If your technology is inflexible, you’ll struggle to integrate custom features or scale the product as your user base grows. Worse, a poorly built platform could lead to outages or financial inaccuracies that damage your reputation.

Mitigation

Invest in a robust, customizable technology stack. Ideally, work with a proven prediction market core that you can tailor to your specific needs. The optimal approach, as Vinfotech suggests, is to “start from a refined core, then customize aggressively”.

This gives you the best of both worlds: a battle-tested engine and the flexibility to add unique features or adapt to local requirements. For example, a strong core should cover the end-to-end market lifecycle – “Create markets → Take trades → Manage balances → Resolve outcomes → Settle winnings” – reliably and at scale. With that in place, you can focus on customization like user experience, unique market types, or regional integrations without risking the platform’s stability.

Remember that building from scratch can take 6–12 months due to the complexity of settlement and security, whereas leveraging an existing core can cut launch time dramatically. Crucially, a quick script is not worth it if it “fails under load or lacks necessary security” – serious operators need a solid engine.

By opting for custom development on a strong foundation, you ensure your platform is scalable, secure, and capable of offering all the features (from order books or dynamic pricing to back-office controls) that a modern prediction market demands. In essence, don’t cut corners on technology – a custom-built solution aligned with your vision will save you headaches and allow your business to grow confidently.

Strategic Mitigation: Source Code Ownership

The robust alternative is Source Code Ownership. This model, championed by Vinfotech, delivers the enterprise-grade control necessary for long-term viability.

Vinfotech’s Infrastructure Advantage:

# Asset Value: Owning the source code transforms the technology from an operational expense into a balance sheet asset. The operator can modify, audit, and perfect the code without external dependencies.

# Custom Scalability: Vinfotech’s centralized solution is optimized for high-frequency trading, avoiding the latency and gas costs of decentralized protocols while offering the ability to scale vertically or horizontally on the operator’s own cloud infrastructure (AWS, GCP).

# Security Audits: With full code access, operators can conduct independent penetration testing and security audits, a requirement for obtaining licenses in tier-1 jurisdictions like the UK or US states.

# No Recurring GGR Share: Vinfotech operates on a development fee model, meaning the operator keeps 100% of the upside. This economic efficiency is critical for surviving the low-margin early days of a marketplace.

4. Inadequate Market Resolution and Data Integration

Pitfall

Nothing will sink user trust faster than a market that doesn’t resolve correctly or on time. In prediction markets, market resolution is the process of determining the outcome of a bet or contract and settling it – if this mechanism is weak, you invite disputes and skepticism.

A pitfall to avoid is relying on manual resolution or a single unreliable data source. Operators who wait hours or days to declare winners (perhaps due to a lack of integration with live data) will frustrate users. Even worse, if outcomes are called wrongly due to poor data or bias, your platform’s credibility could be irreparably damaged.

Prediction markets require handling real-world event data (sports scores, election results, etc.) that can change quickly, so failing to integrate real-time data feeds or independent sources is a critical mistake. As industry experts emphasize, “integrity is the currency” of these markets – if users suspect that results are manipulated or errors are common, they won’t return.

Mitigation

Set up a robust, transparent resolution workflow backed by reliable data. First, define clear resolution criteria for every market at the time of creation (e.g., which official source or oracle will be used to verify the outcome, and at what time). Then, integrate external data feeds or APIs to automatically fetch results as soon as they are available.

Modern prediction market platforms often provide “real-time data feeds” via APIs and WebSockets to update market status instantly. Ensure your system can ingest these feeds and trigger settlements without manual intervention, while still allowing manual oversight for edge cases. A good platform will also include a dispute resolution process – for instance, Vinfotech’s solution offers “role-based overrides, clear data sources, and a full audit trail for transparency” in case any outcome is contested. This kind of audit trail and dispute workflow is essential for maintaining fairness and addressing any challenges to results.

Furthermore, consider leveraging AI to assist in market resolution. Some cutting-edge operators (like Slips in the U.S.) are now using AI to “audit and resolve outcomes in real time,” which can greatly shorten dispute windows. Large language models (LLMs) can scan news and official reports to help confirm outcomes quickly. However, if you use AI, make sure to have guardrails and human oversight – automated systems must be fed reliable sources of truth and have exception handling, or else “bad resolutions” can occur if the AI misinterprets something.

In summary, plan for fast and fair resolution of markets. Integrate trustworthy data feeds, use independent oracles where possible, and maintain transparency through logs and dispute mechanisms. By doing so, you uphold the integrity of your market – which directly affects user retention and legal compliance.

Vinfotech’s Resolution Workflow: Vinfotech’s platform architecture addresses the Oracle Problem through a sophisticated Market Resolution & Dispute Workflow.

1. Defined Data Sources: The platform allows operators to hard-code primary and secondary resolution sources (e.g., "Primary: AP News; Secondary: Reuters"). This reduces ambiguity by binding the outcome to specific URLs or APIs.

2. Role-Based Overrides: While automation is the default, Vinfotech provides a "human-in-the-loop" capability. Admins with specific permission levels can intervene to override an oracle feed if it is clearly erroneous (e.g., an API glitch). This hybrid model prevents the "stupid smart contract" problem where obvious errors are executed irrevocably.

3. Audit Trails for Disputes: To build trust in a centralized or hybrid model, transparency is key. Vinfotech’s system logs every step of the resolution process. If a dispute occurs, the operator can publish the audit trail showing exactly which data source was used and at what timestamp, inoculating themselves against claims of bias.

4. Clear Rule Sets: The system encourages the creation of "Rules of Engagement" for every market. By forcing operators to define edge cases (e.g., "What if the game is cancelled?") before the market opens, the platform minimizes the surface area for ex-post disputes.

5. Limited Payment Options and Poor User Onboarding

Pitfall

You could build the perfect prediction engine, but it won’t matter if users can’t easily deposit funds, place trades, and withdraw winnings. A pitfall many new platforms face is offering limited payment methods or a clunky onboarding process. This is especially problematic if you aim to launch in multiple regions – users in the US, Latin America, or South Africa might each favor different payment systems (credit cards, e-wallets, bank transfer, mobile money, cryptocurrencies, etc.). If you only support one or two options, you’ll alienate a portion of your potential audience.

Additionally, ignoring Know-Your-Customer (KYC) and anti-fraud measures at the start can lead to compliance trouble or fraud incidents once you scale. Some operators delay implementing KYC to reduce friction, but then face issues with regulators or find themselves scrambling to integrate identity verification later under pressure.

Essentially, a platform without smooth, secure payment and wallet functionality is not truly launch-ready. As one development roadmap put it plainly: “A platform is ‘launch ready’ only when funds move safely.” If users struggle to add money or fear they won’t get paid out promptly, they simply won’t engage.

Mitigation

Integrate multiple payment gateways and streamline the user onboarding/KYC process. Before launch, decide which payment methods are critical for your target markets and ensure your platform supports them. This often means integrating with a mix of payment providers – for example, enabling credit/debit card processing, bank transfers, popular e-wallets like PayPal or Skrill, and region-specific options (like PIX in Brazil or M-Pesa in parts of Africa).

Vinfotech’s implementation typically will “integrate the payment gateway of your choice” and “link with the KYC provider required for your target region” as part of the final launch preparations. On the user side, make the deposit and withdrawal flows intuitive and fast, with clear information on any fees or limits. Simultaneously, bake in compliance by incorporating KYC identity verification early in the user journey (e.g. at signup or first withdrawal) so that you’re operating within legal parameters.

It’s worth noting that successful new platforms showcase these capabilities: for instance, Slips (a P2P betting startup) launched with modern conveniences like Apple Pay, card payments, and ACH, and it built a “payments + KYC stack” from the start to be “real-money, compliance-aware”. This foresight not only appeases regulators but also gives users confidence that their money is safe. Moreover, seamless wallet management (with audit-proof ledger accuracy) is key – double-check that your wallet system correctly handles deposits, holds, payouts, and refunds in all scenarios.

By offering diverse payment options and a frictionless, secure onboarding, you widen your potential user base and remove barriers to participation. In essence, make it as easy and safe as possible for users to get on board and transact, and you’ll significantly improve your platform’s adoption and credibility.

6. Overlooking AI and Market Expansion Tools

Pitfall

In a fast-moving market landscape, failing to innovate can be a pitfall in itself. One emerging area in prediction markets is the use of AI to expand market offerings and streamline operations. If you rely purely on manual market creation (where admins have to dream up questions or events to list) or manual oversight for every outcome, you may struggle to scale your platform or keep users engaged.

A limited catalog of markets (“surface area”) is a risk – users might lose interest if only a few events are available to trade on. Likewise, if your team can’t keep up with verifying outcomes quickly or handling disputes, the user experience suffers. Essentially, not leveraging automation and AI where appropriate can lead to higher operating costs and a stagnant product.

In contrast, competitors who use AI can rapidly generate markets on trending topics and cater to user interests in real time. They can also automate resolution checks to some degree, allowing them to host a larger number of markets without a proportional increase in support staff. Overlooking these tools means risking being outpaced by more innovative platforms.

Mitigation

Leverage AI and smart automation to enhance your platform’s breadth and efficiency, while maintaining quality control. For instance, consider using AI algorithms or language models to monitor news, social media, and user suggestions to auto-generate new markets around trending topics.

Slips, the Los Angeles-based platform, did exactly this by unveiling “AI-generated prediction markets that (a) auto-create new markets around trending topics and storylines, (b) audit and resolve outcomes in real time, and (c) scale beyond sports into politics and finance,” all fueled by integrations with large language models. This approach dramatically increases the volume and variety of markets (the “surface area”) and keeps the content fresh for users.

More markets mean more opportunities for engagement, which in turn can help liquidity as well (because users find something that interests them). Additionally, AI can assist in market resolution by quickly gathering data from predefined reliable sources and even detecting anomalies or potential disputes. That said, it’s crucial to implement such systems with oversight – have clear guardrails, human review processes, and fallback criteria for when AI is unsure.

The goal is to “industrialize market ops” without producing “bad markets and bad resolutions if guardrails fail.” In practice, this might mean AI proposes a market or a result and a human moderator approves it, or that AI only covers straightforward cases while flagging edge cases for manual review. Beyond AI, also use other tools to boost engagement: gamification and community features (leaderboards, social sharing, discussions) can make participation habitual and bring in more liquidity organically.

Many modern platforms run free-to-play contests or prediction tournaments alongside real-money markets to attract a broad audience and then channel them into the paid markets. These strategies mitigate the risk of slow growth by ensuring there’s always something interesting happening on your platform.

In summary, don’t ignore the power of AI and modern engagement tools in your prediction market business. They can vastly increase your capacity and appeal – just implement them thoughtfully to enhance (and not undermine) the user experience.

7. The Engagement Gap and the "Boring" Financial Product

Pitfall

A critical mistake made by operators with a finance background is assuming that the "trading" mechanism itself is entertaining. For the vast majority of retail users, it is not. Financial markets are stressful, complex, and intimidating. A platform that looks and feels like a Bloomberg terminal will fail to retain the casual user, who is essential for liquidity.

The Retention Crisis: Data indicates that while the prospect of profit drives acquisition, it is the experience of play that drives retention. Pure prediction markets suffer from high churn because the feedback loop is often too slow. If a user bets on the US Election in January, they may have nothing to do until November. Without intermediate engagement triggers, they will leave the platform and take their capital with them.

The Gamification Imperative: Successful consumer apps, from Duolingo to Starbucks, rely on gamification—streaks, badges, leaderboards, and social loops—to keep users engaged. The "Octalysis" framework of gamification suggests that drives like "Social Influence," "Scarcity," and "Unpredictability" are more potent than simple "Ownership" (profit).

Mitigation

Operators must pivot from building a "market" to building a "gaming ecosystem." Vinfotech’s Gamification Suite: Vinfotech positions its solution not just as a trading engine, but as a Fantasy Super App that integrates multiple engagement loops.

# Free-to-Play (F2P) Tournaments: Vinfotech’s module allows operators to run risk-free prediction tournaments. Users predict outcomes for points or prizes. This serves as a powerful funnel, converting casual users who are afraid of losing money into educated participants who eventually graduate to real-money trading.

# Streak Mode: To solve the "dead time" problem, the platform supports daily check-in challenges or "streak" questions (e.g., "Will Apple close green today?"). This builds a daily habit, ensuring the user opens the app every morning.

# Leaderboards and Social Proof: Public leaderboards that track not just profit, but prediction accuracy or "wins in a row," create social status. Vinfotech’s social modules allow users to share these achievements, creating organic viral loops.

# Matchday Pools: For sports-focused operators, Vinfotech integrates "pick'em" style pools alongside the prediction market. This captures the casual fan who understands a bracket challenge but not a binary option spread.

By layering these game mechanics over the financial engine, the operator transforms the platform from a utility into a pastime.

8. Market Integrity and Insider Trading Vulnerabilities

Pitfall

Prediction markets face a unique threat that traditional financial markets have spent decades combating: Material Non-Public Information (MNPI). In a stock market, insider trading is illegal and policed. In a prediction market—especially one covering geopolitical events or niche topics—the definition of an "insider" is blurry, and the policing tools are often non-existent.

The "Maduro Whale" Scenario

In 2025, the "Maduro Whale" incident highlighted this vulnerability. A trader made massive profits betting on obscure political moves in Venezuela, raising suspicions of having privileged government information. While "informed trading" makes markets efficient, "insider trading" makes them predatory. If retail users believe the game is rigged by insiders who know the outcome in advance, they will exit the ecosystem.

The Surveillance Gap

Most off-the-shelf prediction market scripts lack the sophisticated surveillance tools used by traditional exchanges (e.g., NASDAQ's SMARTS). They cannot detect "syndicates" (groups of accounts trading in concert) or "layering" (placing fake orders to move price).

Mitigation

Operators must implement proactive surveillance and risk management protocols.

Vinfotech’s Integrity Modules: Vinfotech’s backend empowers operators to act as true market supervisors:

# Exposure Caps: Operators can set limits on how much a single account can wager on a specific market. This prevents a single "whale" (insider) from blowing out the liquidity pool or moving the price to 99% based on private knowledge.

# Circuit Breakers: The system can be configured to auto-pause trading if prices move beyond a certain standard deviation within a short timeframe. This gives the operator time to investigate if the move is due to public news or potential manipulation.

# Granular Access Control: To prevent internal corruption, Vinfotech’s backoffice utilizes strict Role-Based Access Control (RBAC). The staff member who settles the market should not be the same person who can view user positions. This internal wall is essential for maintaining integrity.

9. Monetization Misalignment and the Fee Structure Fallacy

Pitfall

The final pitfall is a failure to design a sustainable economic engine. Many operators launch with a simplistic view of revenue—often just a flat fee on winnings—without realizing that this model can actively suppress liquidity or fail to monetize the platform's utility. A robust prediction market business must leverage sophisticated financial models like Maker-Taker Fees and AMM Spreads to align operator incentives with market health.

Mitigation

The Power of the Maker-Taker Model

In financial markets, not all volume is created equal. "Makers" are users who place limit orders (e.g., "I will buy 'Yes' at $0.40"), adding liquidity to the order book. "Takers" are users who accept those orders (e.g., "I will sell 'Yes' at $0.40 right now"), removing liquidity. A common pitfall is charging both groups the same fee, which disincentivizes the Makers who are essential for a healthy market.

How it Generates Revenue & Liquidity: Successful exchanges often employ a Maker-Taker Fee Structure.

# Taker Fees: The operator charges a higher fee (e.g., 0.2% - 0.5%) to the Taker who demands immediate execution. This is the primary revenue source.

# Maker Rebates: The operator charges a lower fee (e.g., 0% or even a negative fee/rebate) to the Maker. This incentivizes users and market-making bots to populate the order book, tightening spreads.

Vinfotech’s Capability: Vinfotech’s Dynamic Pricing & Order-Book Engine allows operators to configure these fee structures with granular precision. An operator can set a "Taker Fee" of 2% on niche markets to cover risk, while offering a "Maker Rebate" of 0.5% on high-profile election markets to attract massive liquidity. This flexibility ensures the operator can subsidize liquidity where it is needed while monetizing volume where it is plentiful.

Monetizing Automated Market Makers (AMMs)

For long-tail markets where organic order book liquidity is thin (e.g., "Will it rain in London next Tuesday?"), operators often rely on AMMs. The AMM acts as the "House" or protocol that is always willing to trade. The pitfall here is failing to monetize the AMM correctly, exposing the operator to risk without reward.

Revenue via Spreads and LP Fees:

# The Spread: The AMM quotes a buy price (e.g., $0.48) and a sell price (e.g., $0.52). The $0.04 difference is the "spread." As users trade back and forth, the AMM captures this spread as revenue.

# Protocol Fees: In DeFi-style prediction markets, the operator can code a "Protocol Fee" into the smart contract or matching engine. For every trade that hits the AMM liquidity pool, a small percentage (e.g., 1-2%) is siphoned off to the operator's treasury before the rest goes to the Liquidity Providers (LPs).

Vinfotech’s Advantage: Vinfotech’s platform supports hybrid monetization. Operators can act as the sole Liquidity Provider (LP) on their own AMM, effectively capturing 100% of the trading spreads and fees, similar to a traditional sportsbook "overround" but with the transparency of a market mechanism. Alternatively, they can open the pool to users and take a "management fee" for facilitating the market. This ability to switch between "Exchange Model" (Maker-Taker) and "House Model" (AMM) based on the specific market type is a critical strategic lever provided by Vinfotech’s custom architecture.

Conclusion: The Architecture of Resilience

The launch of a prediction market business is a high-stakes venture. The sector offers the potential for exponential growth, driven by a global appetite for speculative entertainment and the financialization of truth. However, the graveyard of failed platforms serves as a testament to the complexity of the task. Operators must navigate a minefield of regulatory bans, liquidity droughts, oracle failures, and retention crises.

The unifying theme across all seven pitfalls is the danger of rigidity. Rigid legal interpretations, rigid liquidity algorithms, rigid user interfaces, and rigid SaaS infrastructure are the points of failure.

To survive and thrive, operators must prioritize flexibility and control.

Regulatory Flexibility: The ability to geo-fence and toggle modules instantly.

Liquidity Flexibility: The ability to mix AMMs, human makers, and bots.

Product Flexibility: The ability to gamify and cross-sell.

Technical Flexibility: The ability to own the code and control the roadmap.

The Vinfotech Proposition

Vinfotech stands out as a strategic partner capable of delivering this requisite flexibility. By offering a custom-built, centralized solution with full source code ownership, Vinfotech addresses the structural risks of the industry head-on. Their suite of modules—from F2P tournaments and gamification to sophisticated risk management and compliance tools—provides the operator with an arsenal of mitigation strategies.

In an industry where the rules are being rewritten in real-time, the ultimate competitive advantage is the ability to adapt. For the operator looking to build a durable prediction market ecosystem in 2026, owning the technology is not just an IT decision—it is the fundamental hedge against extinction.

Appendix: Technology Stack Comparison for Prediction Markets