Forkast has launched ATLAS, an autonomous trading system built for prediction markets tied to esports, cryptocurrency, and major global sports events, including the World Cup, as competition intensifies across one of the fastest-growing segments of digital markets.
The platform, introduced Tuesday, allows users to create and deploy automated trading agents that can follow preset strategies, operate around the clock, and compete for market-based rewards. ATLAS stands for Adaptive Trading & Learning Agent System, and Forkast says the product is designed to give individual traders access to automation tools that have typically been associated with more sophisticated trading operations.
Users can configure each agent by setting a market focus, risk preferences, and trading rules. Once deployed, the agents are designed to act independently within supported prediction markets. Forkast says the system includes memory and self-improvement features, meaning agents can adapt based on prior outcomes and performance data. The company also said the underlying architecture can support coordination among multiple agents in future versions.
The launch comes as prediction markets are drawing much heavier activity. Data from industry researchers show trading volume in the sector rose from less than $5 billion in September 2025 to about $24 billion in April 2026. Separate market tracking also showed monthly volume reaching roughly $25.7 billion in March, underscoring the speed at which outcome-based contracts have moved from a niche product into a larger trading category.
That growth has attracted more professional firms, regulated platforms, and algorithmic trading teams. As a result, independent traders using slower manual interfaces face a more competitive environment, particularly in markets where odds can shift rapidly after new information emerges.
Forkast is positioning ATLAS as a way to narrow that gap, though the product does not eliminate the risks of automated trading. Speed can help traders react faster, but it can also accelerate losses when a strategy is poorly designed, a data signal is misread, or market liquidity changes suddenly.
A push into automated prediction markets
Prediction markets allow traders to take positions on the probability of future outcomes. These outcomes can include sports results, player statistics, election-related events, economic data, cryptocurrency milestones, or live entertainment and esports developments.
Unlike traditional sports wagering, many prediction markets operate through financial-style contracts that trade based on changing probabilities. A contract’s price often reflects the market’s implied view of whether an event will happen. If odds move from 40 percent to 60 percent, the contract price may move in a similar direction, creating trading opportunities before the event is resolved.
ATLAS is designed to let users automate participation in these markets rather than manually clicking through orders. Traders can define conditions under which an agent enters or exits a position, how much risk it can take, and which types of events it should monitor.
Forkast says the system also includes integrated dashboards so users can configure agents, monitor performance, and review market behavior. The company’s broader roadmap centers on combining automation with skill-based progression systems, aiming to reward effective strategy design rather than high trading frequency alone.
The company said ATLAS agents are now publicly available through Forkast’s official website.
Esports becomes an early testing ground
Forkast is giving ATLAS an initial focus on esports, a market it describes as fast-growing but still underserved by advanced trading infrastructure.
Esports markets can move quickly because live outcomes are affected by player performance, team strategy, in-game momentum, and sudden shifts during matches. A single early objective, player elimination, or tactical error can change the probability of a match result within seconds.
To support these markets, ATLAS integrates data from GRID, a provider of high-frequency esports datasets. GRID’s data is expected to support markets linked to player statistics, match performance, and live in-game outcomes.
Forkast said new player performance markets will also launch alongside ATLAS. These markets will allow traders to take positions on factors such as kills, first blood, and MVP outcomes. In esports, these statistics can be as important to traders as the final match result because they create more granular opportunities across a live event.
The product also includes a real-time visual tool called the “Battle Bar,” which maps market movement and displays live odds shifts between 0 and 100 percent. The tool is meant to help users follow changing probabilities more clearly as an event unfolds.
Trading league adds a competitive layer
Forkast also plans to host the TVT Trading League, a structured competition in which users deploy automated agents against one another in live markets. Rewards will be denominated in USDC, a dollar-linked stablecoin widely used across digital asset platforms.
The league format is designed to make algorithm design part of the competition. Participants will create, adjust, and refine their automated systems while the agents execute trades in real time.
That approach reflects a broader shift in digital markets, where trading is increasingly shaped by automation, data feeds, and strategy logic rather than manual execution alone. In fast-moving prediction markets, especially around live sports and esports, timing can be critical.
According to Forkast, founder Lau has argued that many regular users have struggled in markets where speed and infrastructure matter. Manual traders may be at a disadvantage when competing against systems capable of processing data and sending orders much faster than a person can react. Forkast says ATLAS is intended to address that problem by allowing users to predefine strategies and execute them automatically.
Still, faster order placement is not the same as guaranteed better performance. Automated tools can reduce reaction time, but they can also magnify errors. A bot that follows weak instructions will simply execute those instructions faster. Traders using automated systems typically need to pay close attention to position sizing, loss limits, data quality, and how the system behaves during unusual market conditions.
Sports demand boosts volume
The launch arrives during a period of strong interest in sports-related prediction contracts. Global football and other major competitions have helped drive activity during the summer, as traders seek exposure to match outcomes and related event markets.
Kalshi, a regulated prediction market platform in the United States, handled $9.4 billion in June volume tied to sports games, according to the figures cited in the original announcement materials. The figure highlights how quickly sports-linked contracts have become a major source of activity for prediction market platforms.
World Cup-related markets are expected to be an important test for trading systems such as ATLAS. Major international tournaments draw global attention, deep discussion, and constant news flow. Team injuries, lineup changes, weather, referee decisions, and live game developments can all move prices.
That combination creates opportunities for traders but also increases risk. Prices can become volatile when markets react to incomplete information or when several traders respond to the same signal at once. Automated systems may help users respond more quickly, but they may also enter crowded trades if many agents are programmed around similar data triggers.
Retail access and institutional-style tools
Forkast’s product messaging emphasizes retail access to tools that resemble those used in more advanced trading environments. Continuous execution, real-time feedback, and automated rules are standard features in many professional trading operations, but they are less common among casual users of prediction markets.
ATLAS is part of an effort to bring some of those capabilities to a broader audience. The company says users can customize their agents rather than relying on one default strategy. This matters because prediction markets vary widely. A strategy designed for a slow-moving cryptocurrency policy market may not work in a fast esports match. A system that performs well before an event may behave differently when live results are changing every second.
The product also reflects the growing importance of user interfaces in prediction markets. Early platforms often emphasized simple buy-and-sell screens, but higher volume has created demand for dashboards, analytics, alerts, automated order logic, and visual market tools.
Forkast’s Battle Bar, performance dashboards, and agent configuration tools are aimed at that demand. The company is trying to make complex market activity more accessible without requiring every user to build custom infrastructure from scratch.
Risks remain for automated traders
The growth of autonomous agents in prediction markets raises familiar questions from other parts of electronic trading. Automation can improve discipline by removing emotion from execution, but it can also create new failure points.
A trader may set rules that appear sensible in calm markets but break down during highly volatile periods. Data feeds can lag, markets can become thin, and live-event information can change faster than models can properly assess. In some cases, an automated agent may keep trading even when the human user would have paused.
Risk controls are therefore likely to be central to how ATLAS and similar systems are used. Traders who test automated systems commonly begin with small amounts, observe performance across different market conditions, and adjust rules before increasing exposure. Loss limits and diversification across events can also reduce the chance that one bad market or one faulty rule causes outsized damage.
This is especially relevant in esports and cryptocurrency-linked prediction markets, where volatility can be sharp. Player performance markets may be affected by unexpected substitutions, technical pauses, game patches, or tactical decisions that are difficult for a simple rule-based agent to interpret. Crypto markets can also react suddenly to regulatory news, protocol events, macroeconomic data, or social media-driven sentiment.
Forkast’s system is designed to give users more control, but that control requires careful configuration. The most important question may not be whether an agent can trade quickly, but whether its strategy can remain effective when conditions change.
A crowded field is emerging
Prediction markets are no longer limited to small communities of enthusiasts. Higher volume has brought more attention from financial firms, political forecasters, sports traders, crypto market participants, and data providers.
That shift is increasing the value of speed, market access, and reliable event data. It is also making prediction markets more similar to other electronic trading venues, where edge can come from better information, faster execution, stronger risk systems, or more disciplined strategy design.
Forkast’s ATLAS launch fits into that larger trend. By combining autonomous agents with esports data and a competitive league structure, the company is trying to turn prediction market trading into a more interactive and programmable experience.
The platform’s success will depend on several factors, including the quality of its data integrations, the reliability of its execution, the usability of its dashboards, and the ability of traders to build strategies that perform in real markets. The TVT Trading League may also serve as a public test of how well automated agents can compete under live conditions.
For now, ATLAS enters a market that is expanding quickly but still evolving. Prediction markets have shown strong volume growth, especially around sports and live events, but they remain complex, volatile, and subject to changing regulatory and liquidity conditions.
Forkast is betting that automation will become a central feature of the next phase of prediction market growth. For traders, the launch offers a new toolset, but not a shortcut around market risk. The advantage will likely belong to those who combine faster execution with careful strategy design, disciplined exposure, and a clear understanding of how outcome-based markets behave when the action moves in real time.
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