AI Agent

AI Agents

57Blocks enable Web3 projects by building AI agents that enhance automation, security, and engagement.

These agents include: Market Analysis and Trading agents, Yield Farming and Liquidity agents, Compliance and Engagement agents, Contract Auditing and Testing agents, which strengthen security through real-time monitoring and risk management.These AI-driven solutions drive scalability, efficiency, and trust in the Web3 ecosystem.

Blockchain Engineering Services

Market Analysis and Trading
Provide real-time trend analysis and trading predictions
Automate trading with arbitrage and trend-based strategies
Optimize portfolios with AI-driven rebalancing
Yield Farming and Liquidity
Identify yield farming opportunities and compound rewards
Automate liquidity management to minimize losses
Grow treasuries with dynamic yield strategies
Compliance and Engagement
Generate AI-driven content for community updates
Use AI chatbots for support and moderation
Track community sentiment to refine engagement strategies
Contract Auditing and Testing
Detects vulnerabilities and optimize smart contracts
Monitor anomalies in real-time
Use AI to manage risk pools in DeFi insurance

Talent From

57blocks core engineering team members have more than 20 years of experience in the technology solutions industry, the company founder is the former vice president of Adobe China technology to help Adobe build and manage the development team of 200 people. Past experience includes Google, Driscoll's, Fanatics, and other enterprise solutions.

GoogleStanford UniversityAdobeBerkeleyFanatics

Insights From Building

Using just an image on a mobile device, the search application is designed to return matches from the database that are either identical or resemble the original uploaded image. In this blog, we describe the technology behind this powerful functionality.

Image Quality Assessment (IQA), specifically Objective Blind or no-reference IQA, is a crucial function in determining image fidelity or the quality of image accuracy. Further, IQA helps maintain the integrity of visual data, ensuring its accurate representation. In this article, we share an analysis of the best machine learning models that support IQA, including BRISQUE, DIQA, NIMA and OpenCV. We will delve deeper into their operations, the challenges and advantages, and their significance in the ever-evolving field of image quality assessment.

Using just an image on a mobile device, the search application is designed to return matches from the database that are either identical or resemble the original uploaded image. In this blog, we describe the technology behind this powerful functionality.

Image Quality Assessment (IQA), specifically Objective Blind or no-reference IQA, is a crucial function in determining image fidelity or the quality of image accuracy. Further, IQA helps maintain the integrity of visual data, ensuring its accurate representation. In this article, we share an analysis of the best machine learning models that support IQA, including BRISQUE, DIQA, NIMA and OpenCV. We will delve deeper into their operations, the challenges and advantages, and their significance in the ever-evolving field of image quality assessment.

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