Cipher9 Partners with Goooo to Build AI Research Labs, Exploring Next-Generation Intelligent Trading Infrastructure

SINGAPORE, July 02, 2026 (GLOBE NEWSWIRE) -- Goooo, a prediction market aggregation infrastructure, has entered into a strategic partnership with investment firm Cipher9. The two parties will jointly establish Goooo AI Research Labs, focusing on long-term research and development in AI Agents, autonomous trading agents, AI-driven quantitative research, and predictive intelligence infrastructure. As a key component of this collaboration, Cipher9 will invest $2 million in Goooo to support related technology research, product development, data infrastructure construction, and global talent acquisition.

According to the plans of both parties, this investment will be deployed in phases based on research progress, technology implementation, and ecosystem development needs. Goooo AI Research Labs will take responsibility for frontier research, technology validation, product incubation, and ecosystem collaboration, driving research outcomes into real market environments and gradually forming continuously evolving product capabilities.

The first phase of the lab will focus on five key areas: AI Agent autonomous decision-making systems, AI-driven trading model research, multi-market prediction and strategy optimization, data analysis and quantitative research frameworks, and AI integration with on-chain prediction markets. Related research will cover market information understanding, probability assessment, strategy generation, risk management, trade execution, and outcome feedback, forming a complete technology pipeline across research, decision-making, and execution.

Through this investment and joint research initiative, Cipher9 and Goooo will jointly advance the application of AI Agents in prediction markets and intelligent trading scenarios, further improving AI trading infrastructure for developers, institutions, and global users.

Why Establish AI Research Labs?

As various AI solutions continue to evolve, the application of artificial intelligence in finance is gradually expanding from information retrieval, content summarization, market analysis, and investment research assistance toward continuous decision-making and real-world execution. The maturity of model reasoning, tool calling, long-term task execution, and multi-agent collaboration enables AI systems to continuously acquire market information, understand event changes, break down research tasks, and generate strategies and execution plans based on predefined objectives.

In December 2025, the Data Intelligence Laboratory team at the University of Hong Kong released the AI-Trader benchmark, conducting real-time evaluations of the autonomous trading capabilities of six major large language models across U.S. stocks, A-shares, and crypto markets. The results showed that model performance in risk management, dynamic market adaptation, and cross-market execution directly affected final returns.

At the same time, the demand for AI in financial scenarios is also evolving from early-stage one-time analysis toward continuous market monitoring, multi-source data processing, strategy research, risk parameter management, trade execution, and outcome feedback. Agents are gradually becoming a key layer connecting these processes.

As a prediction market infrastructure project, Goooo has long focused on prediction market aggregation, event data, probability analysis, strategy research, and intelligent execution, while continuously exploring how AI Agents can enter real market environments. Its existing products and data foundation enable related research to directly connect with real-world events, market prices, liquidity changes, and trading outcomes, allowing testing and iteration in practical scenarios.

The Goooo team stated: “Through our long-term exploration and practice in prediction markets, we have found that prediction markets provide a clear validation environment for autonomous trading systems. Prediction markets are built around real-world events, typically featuring clear outcomes, deadlines, and settlement rules. The performance of Agents in information understanding, probability assessment, position allocation, and execution paths can all be compared against final outcomes after events conclude, creating a complete research, validation, and feedback loop.”

Taking Prediction Arena as an example, multiple frontier models have operated with real funds on Kalshi and Polymarket for 57 consecutive days, with significant differences emerging in their final performance. These results further demonstrate that market selection, probability calibration, position management, and execution quality directly impact the actual performance of Agents in real markets.

Based on a shared understanding of these trends, Cipher9 and Goooo have decided to jointly establish Goooo AI Research Labs. Leveraging Goooo’s existing product foundation, market environment, and technology validation capabilities, together with Cipher9’s resources in funding, institutions, and ecosystem partnerships, the lab will continue advancing research and development in AI Agents, autonomous trading systems, quantitative research, and intelligent trading infrastructure, while gradually bringing related achievements into real products and market applications.

Key Research Directions of AI Research Labs

AI Agent Autonomous Decision-Making Systems

A single decision in financial markets usually involves multiple types of information, including event developments, real-time market conditions, on-chain capital flows, market sentiment, historical data, and account status. AI Research Labs will focus on researching how AI Agents understand user intentions and market environments, and organize complete research and decision-making tasks around specific objectives.

For example, when users want to continuously track changes in a specific policy or identify price differences of the same event across different markets, the Agent can identify the event subject, timeframe, and risk preferences, retrieve relevant data, and break the objective down into specific processes such as event research, market comparison, probability analysis, risk assessment, and execution planning. This allows natural language user requests to be transformed into structured, verifiable, and executable workflows.

AI-Driven Trading Model Research

AI Research Labs will study how to combine the information understanding capabilities, market analysis capabilities, and trading models of large language models to process news, market data, on-chain capital flows, macroeconomic data, and sentiment signals in an integrated manner.

Related research will cover signal identification, trading logic generation, model evaluation, risk attribution, and strategy iteration. The research team will continuously analyze the relationships between different information sources and market changes, and transform research outcomes into explainable, verifiable, and reusable trading models, providing a foundation for future strategy execution and product applications.

Multi-Market Prediction and Strategy Optimization

AI Research Labs will integrate multiple prediction markets and real-world events, combining market prices, liquidity, rules, external data, and historical samples to continuously generate dynamic probability assessments and strategy solutions.

When policy changes, economic data releases, corporate developments, or geopolitical events occur, the system can simultaneously track price reactions, capital movements, and information propagation across different markets, updating event probabilities and execution strategies based on new data. Related research will also cover cross-market comparison, position allocation, path selection, and strategy adjustment to improve decision-making and execution efficiency in multi-market environments.

Data Analysis and Quantitative Research Framework

Markets generate large amounts of news, price movements, on-chain capital changes, macro indicators, and social sentiment every day. AI Research Labs will build a unified data analysis and quantitative research framework to clean, correlate, validate, and backtest multi-source data.

This framework will focus on supporting signal extraction, factor analysis, strategy backtesting, model evaluation, risk attribution, and strategy library development. Through standardized data processing and research workflows, the lab can continuously evaluate the effectiveness of different signals and transform research outcomes into reliable analytical tools and quantitative strategies.

AI Integration with On-Chain Prediction Markets

AI Research Labs will research how AI Agents can complete identity verification, user authorization, fund access, risk control, and trade execution in on-chain prediction markets, enabling the integration of intelligent decision-making with real market environments.

In the future, users will be able to define fund ranges, position limits, eligible markets, slippage restrictions, and strategy cycles in advance, allowing Agents to access data, generate strategies, and execute trades within authorized permissions. Related systems will also adapt to order books, AMMs, on-chain protocols, and other market environments, while fully recording strategy generation, risk checks, order execution, and outcome feedback.

This direction will also provide clearer integration methods for external Agents, developers, and institutions, enabling them to use prediction market data and intelligent trading capabilities in an authorized, traceable, and auditable environment.

Building the Next Generation of Intelligent Market Infrastructure

The Goooo team stated: “The future development of prediction markets will increasingly rely on the ability to process complex information, as well as continuous improvements in market risk management and decision-making efficiency. As participants, trading scenarios, and market data continue to grow, artificial intelligence has the potential to become a key force driving the further evolution of the industry.”

Through its partnership with Cipher9, both parties hope to use Goooo AI Research Labs as a long-term research and development platform to continuously explore the application of artificial intelligence in prediction markets and broader intelligent trading scenarios, while gradually bringing related research into products and market environments.

In the future, the research outcomes of AI Research Labs will also gradually become available to the Goooo ecosystem, providing developers, institutions, and partners with more accessible technical capabilities and application support. Through continuous research and ecosystem collaboration, both parties aim to advance intelligent market infrastructure toward a more efficient, open, and scalable future.

Media Contact:
RICKY NG SEE SAN (RICKY HUANG SISHAN)
[e-mail]

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