Decentralised finance (DeFi) is witnessing a fresh wave of innovation in 2025, with one of the most exciting developments being the fusion of DeFi and artificial intelligence (AI) — often referred to as DeFAI.
The DeFAI landscape can be broadly categorised into:
Infrastructure Platforms: Model training and inference, data and security, as well as mechanisms for coordination and collaboration.
Abstraction (general DeFi purpose): Simplify various DeFi activities using natural language commands.
Vertical Applications: Specialised DeFi applications, including yield optimisation and market analysis.
Abstraction protocols currently lead in market cap among DeFAI sub-categories, with five of the top 10 DeFAI players being in the category, holding a combined 46.6% market dominance.
Griffain and HeyAnon are notable abstraction AI platforms based on their leading market cap.
Griffain’s Agent Engine enables personal AI agents to carry out custom instructions tailored to individual needs, as well as special agents designed for specific tasks.
HeyAnon’s AI agent Gemma can analyse a user’s past trading patterns and goals, curating relevant tokens or yield opportunities. Its execution system enables conditional, continuous operations without the user’s active presence.
Crypto.com’s AI Agent SDK is another example of abstraction AI platforms, processing natural language and executing instructions directly, such as calling chain data (e.g., balance enquiry), wallet management (transfer functions), and basic smart contract interactions (swap).
DeFAI is still in its early development phase, with numerous use cases and emerging projects lacking clear differentiation, and many functions yet to be launched. As AI tools advance, DeFi is set to become more intuitive, efficient, and meaningful with real-world applications versus simply simplifying user experiences.
1. Introduction
1.1 What Is DeFAI?
Decentralised finance (DeFi) is experiencing a new surge of innovation in 2025, with one of the most thrilling trends the integration of DeFi and artificial intelligence (AI) — more specifically, agentic AI — commonly known as DeFAI. The DeFAI market cap currently totals U$1.3 billion, according to CoinGecko.
Agentic AI refers to AI systems that can autonomously make decisions and solve complex problems through sophisticated reasoning and iterative planning. It is designed to operate independently, adapting to various challenges without human intervention. Agentic AI enhances the effectiveness of DeFi by providing intelligent automation and decision-making capabilities within decentralised financial frameworks.
The rise of AI agents is the primary driver of DeFAI. In blockchain, agents can interact with smart contracts and accounts to manage complex tasks without constant human intervention.
AI is transforming DeFi in three ways: AI abstraction, autonomous DeFi agents, and AI-driven decentralised applications (dapps).
Automating Trading Strategies: AI-powered bots analyse real-time market data, execute trades, and refine strategies based on predictive modelling.
Enhancing Risk Management: AI algorithms evaluate market conditions and liquidity risks, enabling users to make informed decisions and mitigate potential financial losses.
Optimising Yield Strategies: AI-driven analytics support yield farming, liquidity provision, and staking, maximising returns with minimal manual effort.
Improving Market Analysis: AI models deliver deeper insights into price trends, sentiment analysis, and token performance, facilitating data-driven investment strategies.
2. The Landscape of DeFAI
In general, the DeFAI landscape can be broadly categorised as follows:
Horizontal Platforms: Infrastructure for agent development, including creation, deployment, and management. These platforms encompass model training and inference, data and security, as well as mechanisms for coordination and collaboration.
Abstraction (general DeFi purpose): Projects in this category aim to simplify a broad range of DeFi activities and enhance user accessibility. Abstraction enables users to execute DeFi operations using natural language commands, thereby lowering barriers for both beginners and experienced users alike.
Vertical Applications (specialised DeFi purpose):
Yield Optimisation: Projects in this category leverage AI to optimise yields and portfolio allocation.
Market Analysis and Prediction: Projects in this category focus on aggregating and analysing on-chain data and information from multiple sources to identify trends and opportunities across DeFi and tokens.
3. Case Studies
Half of the top 10 DeFAI players by market capitalisation are abstraction platforms, including Griffain, HeyAnon, ChainGPT, Spectral, and SwarmNode.ai, collectively accounting for 46.6% dominance by market cap, according to CoinGecko.
3.1 Case Study — Griffain
Griffain is one of the largest abstraction AI platforms built on Solana. It introduces a wide range of specialised agents that enable users to execute trades, manage wallets, mint NFTs, and perform token sniping — all through simple natural language commands. However, it is currently in the early access phase and requires an invite to access.
The Agent Engine
The Griffain team advocates the concept of The Agent Engine, which is built upon a network of agents, as well as the concept of a search engine. The network of agents works together to complete tasks, and each agent is specialised in their own area (e.g., delegation agents, search agents, execution agents). The search engine enables users to type in their commands, and it subsequently organises the information to enhance user experience.
Griffain’s network of AI agents consists of two types:
Personal AI Agents: Controlled by users, allowing custom instructions and memory settings to fit personal needs.
Special Agents: Designed for specific tasks, such as:
Airdrop Agent: Finds target addresses and distributes tokens to specific holders.
Staking Agent: Automatically stakes SOL or other assets into liquidity pools for yield farming.
Additionally, Griffain has a multi-agent collaboration system, allowing multiple AI agents to collaborate to perform a wide range of blockchain-related tasks, essential for complex tasks requiring coordinated effort, such as managing crypto wallets, handling transactions, performing token sniping, staking, and many other DeFi activities.
Automated DeFi transactions
Manage crypto wallets, such as checking account balances, viewing deposit history, and more.
Complete transactions using natural language input.
Purchase newly launched meme coins on Pump.fun based on specific keywords or conditions, as well as token staking.
Automated staking and DeFi strategy execution.
Screenshots of Griffain (Source: X.com @0xDefiLeo)
Social media activities:
Agents can help users interact with external systems like social media; for example, sending a tweet on behalf of users.
Data analysis:
Agents can gather data from major platforms for market analysis, such as identifying tokens using keywords and searching for the largest holders of tokens.
Screenshots of Griffain (Source: X.com @0xDefiLeo)
3.2 Case Study — HeyAnon
HeyAnon aims to leverage AI agents to aid users in handling various DeFi functionalities, including trade execution, real-time information aggregation, and portfolio management, etc.
HeyAnon’s Founder, Daniele Sesta, shared his vision for a DeFAI superapp where users can handle all actions, from onboarding to complex on-chain tasks within one unified interface.
Key Features
Details
Personalised agents
– Personalisation: HeyAnon’s Gemma analyses users’ past trading patterns and goals to curate relevant tokens or yield opportunities. – Seamless Execution of Tasks: HeyAnon’s system allows for conditional, continuous operations without user presence, including portfolio rebalancing, monitoring lending positions, and purchasing new tokens.
Natural language execution for DeFi transactions
– Advanced NLP: Enables users to manage DeFi operations through conversational interactions. – Real-Time Data Aggregation: Collects data from multiple platforms for actionable insights. – Multi-Action Execution: Streamlines complex DeFi processes with single prompts. – Protocol Integration: Supports various functions like token bridging, staking, and borrowing.
Data aggregation and insights generation
– Social Channels: Monitors X, Telegram, and Discord for announcements and sentiment changes. – Documentation & Development: Tracks Gitbook updates and GitHub activity, including commits and pull requests. – Price Tracking & Sentiment Analysis: Offers insights on price movements and sentiment trends, helping users correlate market behaviour with community sentiment.
The AUTOMATE Framework
In January, HeyAnon introduced AUTOMATE, a TypeScript framework that enables developers to easily integrate new DeFi protocols into the HeyAnon ecosystem. The framework leverages deterministic logic, where on-chain calls are validated against defined schemes, to ensure the accuracy of on-chain actions. In addition, it supports autonomy within the HeyAnon ecosystem with the following features:
Condition-Based Execution: Agents can rebalance positions, swap tokens, or close out risky trades even when users are offline.
Smart Prompting: Users can just say “Buy coin X” — the agent checks balances, identifies the correct chain, bridges if necessary, and completes the purchase.
Continuous Opportunity Monitoring: The DeFAI agent takes a proactive approach to manage everything, whether it’s automatically purchasing new tokens tweeted by influencers or rotating holdings based on liquidity conditions.
As of January, HeyAnon has integrated a wide array of protocols onto the platform, fulfilling the team’s vision to become blockchain’s abstraction layer for DeFAI.
3.3 Crypto.com’s AI Agent SDK
Crypto.com’s AI Agent SDK aims to empower developers and, ultimately, end-users to interact with the Cronos blockchain and other Crypto.com services by leveraging AI tools as an advanced intermediary. The SDK is able to handle various on-chain functions like calling chain data (e.g., balance enquiry), wallet management (create and transfer funds, get latest block, get transactions by address), and smart contract interactions (swap token, wrapping zkCRO).
Some of the recent notable features include:
Integrate Mistral Models for querying: Mistral Models takes a natural language query, maps it to a blockchain command via DeepSeek, and executes the command.
Integrate multi-large language model (multi-LLM) trips for richer insights and responses, and context support for seamless conversations in a single step. For example, Crypto.com AI Agent integrated Google’s Gemini model for blockchain interactions.
Crypto.com introduced the On-Chain Developer Platform alongside the AI Agent SDK. The On-Chain Developer Platform is a plugin of Cronos-related services, allowing them to connect to different on-chain services like Cronos Explorer.
With the SDK as one of the building blocks, developers can further develop applications leveraging AI and blockchain, including:
Use Cases
Description
Automated Portfolio Management
Continuously scans and generates insights based on on-chain data and automatically executes trades when certain conditions are met.
Blockchain Analytics and Reporting Tool
Acts as a chatbot to transform user questions (e.g., “What is the market capitalisation of Ethereum now?”) into actionable blockchain queries, generating valuable insights on market trends and implications.
DAO Management
Translates governance proposals or community feedback into binding smart contracts, and agents can help to manage the execution.
Content Monetisation
Creators can use this AI agent-empowered wallet to receive tips and payments.
General Commercials
– Embeds crypto payments into shopping, travel services, subscriptions, and more. – For example, AI agents can help to browse through shops to find discounts and initiate payments, or execute travel plans to manage bookings via crypto wallets.
4. Conclusion
DeFAI is still in its early development phase, with numerous use cases and emerging projects lacking clear differentiation, and many functions yet to be launched.
As AI tools continue to progress, though, we anticipate that DeFAI will become more intuitive, efficient, user-friendly, and autonomous. The future of DeFAI is expected to go beyond simply simplifying complexity or improving user experience; it will evolve into a transformative force with increasingly relevant real-world applications. This evolution will accelerate DeFi adoption, making it more accessible to both new and existing users.
Past (without DeFAI)
Future (with DeFAI)
DeFi Complexity
– User knowledge on complicated protocols and architectures are required. – Challenges of navigating wallets and bridges before participating in DeFi.
– Research is done easily through queries and AI agents. – Initial wallet setup and bridging experiences are completely abstracted from the process. – Execution of multi-step processes is triggered with a single natural language prompt.
Manualness & Inefficiency
– Users have to manually keep track of new protocols and opportunities. – Users are required to actively manage their positions and portfolios to minimise risk and losses.
– Agents automatically update users on new DeFi and trading opportunities. – Users can predefine strategies and have them executed autonomously. – Automated rebalancing and position management simplify risk management.
DeFi is witnessing a fresh wave of innovation, with one of the most exciting developments being the fusion of DeFi and AI — often referred to as DeFAI. In this report, we look into the DeFAI landscape, and delve into Griffain and HeyAnon as case studies, both of which are notable examples in the abstraction protocol category.
