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SQHWYD CTO Anya Volkov Outlines Reinforcement Learning-Based Architecture for Cross-Chain Liquidity

 Brand News 24 |  December 10, 2025

Unity Layer(TM) Incorporates Microservices and Multi-Party Computation to Address Security and Latency Challenges in DeFi Infrastructure

Anya Volkov, Chief Technology Officer of SQHWYD GLOBAL Ltd., today presented the technical framework behind the company’s core architecture, the Unity Layer(TM). The presentation focused on the application of distributed systems and machine learning to manage cross-chain liquidity and addressed current technical challenges within digital asset infrastructure.

SQHWYD CTO Anya Volkov Outlines Reinforcement Learning-Based Architecture for Cross-Chain Liquidity

During the technical briefing, Volkov noted that the security and stability of cross-chain bridging protocols remain key focus areas for the industry. She stated that system architecture choices significantly impact asset security and transaction reliability. SQHWYD's technical approach focuses on optimizing resource scheduling through fundamental architecture design rather than relying solely on application-level interface aggregation.

According to the released technical documentation, the Unity Layer(TM) deploys deep reinforcement learning models designed to dynamically analyze and optimize routing paths across Centralized Finance (CeFi) and Decentralized Finance (DeFi) protocols . The system aims to aggregate fragmented liquidity sources to improve the efficiency of order execution.

Regarding system performance and data consistency, Volkov described the platform's adoption of a microservices architecture and in-memory processing technologies. The architecture utilizes asynchronous message queues, such as Apache Kafka, to manage high-concurrency transaction requests, with the objective of maintaining data durability and consistency under high-load environments .

On the topic of security, Volkov emphasized the integration of cryptographic frameworks into the transaction lifecycle. SQHWYD utilizes Multi-Party Computation (MPC) wallet technology. This approach distributes key shards across different nodes for collaborative signing, replacing traditional single-private-key management models to reduce the risk of single points of failure .

About SQHWYD 

SQHWYD GLOBAL Ltd. is a US-registered fintech company focused on developing next-generation digital asset infrastructure. Led by scientists and financial experts, the company's core technology, the Unity Layer(TM), is dedicated to connecting Centralized Finance (CeFi) and Decentralized Finance (DeFi) systems. SQHWYD provides technical solutions including institutional-grade security custody, trade execution, and cross-chain interaction.

Media Contact

Organization: SQHWYD

Contact Person: Marco Ricci

Website: https://www.sqhwyd.net/

Email: Send Email

Address:10200 FOREST GREEN BOULEVARD SUITE 112, LOUISVILLE, KENTUCKY, 40223 USA

Country:United States

Release id:38791

Disclaimer: This press release is provided for informational purposes only and does not constitute investment, financial, legal, or tax advice, and does not form part of any offer or solicitation to buy or sell any financial instruments or digital assets. SQHWYD GLOBAL Ltd. makes no representations or warranties, express or implied, regarding the accuracy, completeness, or future performance of any information contained herein. Digital assets and related technologies may be subject to market, technical, and regulatory risks, and any decisions made in connection with them are the sole responsibility of the relevant parties.

The post SQHWYD CTO Anya Volkov Outlines Reinforcement Learning-Based Architecture for Cross-Chain Liquidity appeared first on King Newswire. This content is provided by a third-party source.. King Newswire is a press release distribution agency. We do not accept any responsibility or liability for the accuracy, content, images, videos, licences, completeness, legality, or reliability of the information contained in this article. If you have any complaints or copyright concerns related to this article, please contact the company listed in the ‘Media Contact’ section above.

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