DWF Labs Partner Lingling Jiang: AI Market Makers Can Connect Fragmented Trading Venues
At the Cointelegraph CONNECT event in Singapore, DWF Labs partner Lingling Jiang stated that AI-driven market makers can connect fragmented trading venues by monitoring a number of markets far beyond human traders' capabilities, thereby helping to improve liquidity across the entire crypto industry.
She pointed out that liquidity fragmentation has long existed in the crypto market, and the RWA sector faces the same issue. Tokenized versions of the same underlying asset lack interchangeability due to different issuers. Although liquidity has improved over the past few years, there is still a long way to go.
AI has shortened research, analysis, and backtesting cycles and can act as a "proxy automated market maker" for individuals to reduce fragmentation, but it is still too early to let AI operate completely autonomously. She also emphasized the security risks brought by AI, stating that teams must view security as an ongoing process rather than a one-time task, establishing strong SOPs at code and human failure points.
Incentive mechanisms are suitable for early liquidity guidance but are not a long-term solution. A sustainable path relies on good fundamentals and community transparency. DWF Labs operates in over 80 centralized and decentralized venues, providing liquidity for over 1,000 projects and maintaining 24/7 global trading with at least 95% uptime.
Market makers (like DWF Labs) continuously buy and sell to provide deep order books and tight spreads, and AI integration expands monitoring and execution capabilities, enabling institutional-level market makers with cross-venue routing capabilities. Beneficiaries are liquidity providers that can scale AI deployment, while those under pressure are traditional market-making structures that rely on a single venue or manual monitoring. The event-driven attributes come from industry conference discussions rather than a single market shock.
DWF Labs has processed over 165 million transactions and provided over $5.8 billion in liquidity support for the global dApp network, while operating simultaneously in spot, derivatives, and OTC markets.
Source: Public Information
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Lingling Jiang joined DWF Labs in 2022, previously working in OTC sales trading for digital assets at OSL, as a forex options trader at Point72, and in derivatives trading at ECLIPSE OPTIONS. Earlier, she also had experience as an assistant trader at BNP Paribas Securities Services and as a buy-side equity analyst at OFI Asset Management. In October 2024, she was promoted to partner in business development, responsible for strategic partnerships and global representation. DWF Labs originated from a high-frequency trading company established in Switzerland in 2018, with a founding team that includes ETH Zurich postdocs and IMC quantitative traders, who have long used AI and machine learning to execute strategies across more than 60 venues.
DWF Labs allocates capital to liquidity provision, venture capital, and incubation. In December 2024, it launched a $20 million AI Agent fund to support autonomous AI projects and is developing an AI trading agent that can fully autonomously manage portfolios, planning to integrate it into its trading workflow. The company provides market making for over 1,000 projects, covering more than 20% of the top 100 projects on CoinMarketCap, while investing $25 million in World Liberty Financial's WLFI and USD1 stablecoin and providing liquidity. Lingling Jiang also serves as a partner at Falcon Finance, promoting synthetic dollars and RWA-related collaborations.
Professional market makers like Wintermute and GSR expanded their shares through high-frequency and cross-venue strategies in the late 2010s, while DWF Labs extends AI from internal quantitative tools to the "proxy AMM" concept. The industry is in a phase of expanding from purely manual/rule-based market making to AI-enhanced cross-venue routing, with DWF Labs occupying an institutional-level liquidity supply position through its coverage of over 80 venues and AI fund layout.
Essentially, this is a technological substitution. AI will expand monitoring and routing capabilities from limited human teams to cover more fragmented venues simultaneously, reducing liquidity islands across issuers and exchanges. The mechanism involves shortening analysis and backtesting cycles and acting as a personal-level proxy, while requiring ongoing security SOPs, shifting capital from manual market making at a single venue to institutional market makers that can integrate multi-market data.
ABAB News · Cognitive Laws
- Monitoring scope determines liquidity; human boundaries are the boundaries of fragmentation.
- Incentives initiate liquidity; fundamentals retain liquidity.
- Tools amplify capabilities; autonomy still requires human-controlled boundaries.