AI Meets Crypto: A Collaborative Vision for Smarter Trading
Ever since ChatGPT began to gain mainstream attention back in 2023, artificial intelligence has been top of mind for all types of technology industries. Today it seems that everyone is striving to integrate AI into their own sector in order for their work to benefit from improved efficiency and accuracy. The blockchain industry is no different, and cryptocurrencies in particular seem to present a great “product-market fit” alongside artificial intelligence. Since crypto is fundamentally an industry based on financialization, the developments being made in AI and machine learning have allowed crypto users to significantly enhance their investment approach toward the markets.
Since early 2024, Bella Protocol has been hard at work in researching and building AI agent tools to facilitate smarter trading. Alongside our partner Phoenix Global, a leading provider of AI infrastructure for blockchain projects, we have released the Bella Signal Bot and LLM Research Bot to grant our community both quantitative and qualitative approaches to crypto trading. As we continue to achieve new milestones in our R&D towards AI, the future of decentralized AI tools is more promising than ever.
History of Crypto Trading Technology
Early Days
Crypto enthusiasts today are likely inundated with a plethora of trading tools and exchanges fighting for their attention, but the early history of Bitcoin presented a vastly different investment landscape. When Satoshi Nakamoto launched Bitcoin’s software in January 2009, the only ways to acquire BTC were to mine it personally or arrange a peer-to-peer (P2P) trade through internet forums. These peer-to-peer trades carried inherent risks as they relied on trust between the parties involved. However, the stakes were relatively low at the time since each bitcoin had little to no monetary value.
Eventually the earliest crypto exchanges like Mt. Gox began to attract users. The majority of trading during those times still relied on peer-to-peer transactions because platforms lacked a primary counterparty or order book. Even following the infamous Mt. Gox hack and rise of modern CEXes like Coinbase and Binance, crypto trading mostly required manual research, technical analysis, and transaction execution. This is how terms like DYOR (do your own research) became popularized — because information about new tokens and the act of placing a trade all relied on manual completion and personal trading strategies.
Rise of Trading Bots
Quantitative trading only became a widespread practice several decades ago, and it was mostly used in traditional finance markets. Around the late 2010s, the earliest crypto trading bots came into being. They were simple, rule-based tools that operated on fundamental strategies like moving averages, support and resistance levels, and the Relative Strength Index (RSI). These bots were programmed to perform specific actions when certain market conditions were triggered. For instance, traders could configure the bot to buy when a cryptocurrency’s price moved above a moving average or sell when the RSI hit a predefined level. Although these bots worked well in specific situations, they lacked adaptability and struggled to account for multiple variables simultaneously. Centralized exchanges also released their own grid trading bots, allowing users to implement grid trading strategies at pre-defined price levels.
As cryptocurrency markets grew and arbitrage opportunities arose, arbitrage bots were created to exploit price discrepancies for the same asset across various exchanges. They automatically bought at a lower price on one platform and sold at a higher price on another to secure a sure profit. Compared to rule-based bots, arbitrage bots were more sophisticated because they required quick execution and the capability to monitor multiple exchanges simultaneously.
AI Agents
The evolution of crypto trading bots reached a pivotal moment with the introduction of algorithmic trading and artificial intelligence. AI-powered agents surpass basic rule-based commands by integrating advanced mathematical models and technical indicators to guide trading decisions.
- Technical Indicators: AI agents can analyze multiple technical indicators simultaneously, enabling them to better evaluate market sentiment, momentum, and volatility.
- Machine Learning: AI agents utilize machine learning algorithms in order to adapt and refine their strategies based on market data. By continuously iterating and improving upon real-time feedback, they grow even more effective over time.
- Sentiment Analysis: Incorporating tools to evaluate news sentiment and social media trends, AI agents can respond instantly to breaking news or online chatter. Some have even become influencers themselves through automated social media posts containing insights on market intelligence.
AI Trading Agents by Bella and Phoenix
The advanced evolution of crypto trading through AI agents can be best exemplified through the Bella Signal Bot and LLM Research Bot. Bella Protocol collaborated with Phoenix Global and leveraged its institutional-grade AI platform AlphaNet to release the Signal Bot. Having racked up 54,000+ monthly users and 61,000+ subscribers in just half a year after launch, the Bella Signal Bot has aided crypto traders of all backgrounds make trading decisions. It incorporates 5 separate advanced machine learning models. ViperAI features deep learning-based AI signal & strategy for capturing directional alpha, KnightML provides AI-based directional signaling based off deep learning technology and 180+ data points, AI MeanRev takes advantage of rangebound and oscillating markets, Directional Risk predicts where positive and negative trendlines might conflict, and OptimaShort finds a superior edge during bearish and downtrend market environments.
Likewise, Bella’s LLM Research Bot was developed in coordination with Phoenix’s SkyNet — the premier AI compute layer for research tasks. Designed for Retrieval-Augmented Generation (RAG), the research bot excels in text searches and provides seamless access to real-time, trading-focused data directly in the subscriber’s telegram channel. It can now track smart money whales by showing the top 100 holders of popular tokens alongside transaction data. Users of Bella AI agents have benefited from integrating artificial intelligence into their daily trading workflows. The Signal Bot and Research Bot are both user-friendly because their entire user interface is directly accessible in Telegram. The Signal Bot supports 19 trading pairs and only delivers trading signals for the pairs that the user chooses to subscribe to, and only at the most opportune times based on market data. Meanwhile, the LLM Research Bot functions as a personal assistant that users can chat to and obtain crypto-related answers straight from Telegram messenger. As AI continues to expand in capacity and capability, Bella Protocol is already positioned at the forefront to adopt new developments into palatable features benefiting the crypto trading community.
About Phoenix
Phoenix is a leading DePIN and AI infrastructure project, building a scalable computing network for next-generation AI applications and agents. Its flagship SkyNet platform powers industry-specific solutions, including AI-driven trading (AlphaNet, Hypermatrix, Archimedes AI), generative AI (Phoenix GenAI, Phoenix LLM), and decentralized science (TandemAI). By merging decentralized computing with AI innovation, Phoenix is redefining the future of trading, research, and beyond.
About Bella
Aiming to help users simplify crypto trading and optimize crypto yields across multiple chains, Bella Protocol now offers a powerful suite of streamlined tools, including the AI-powered Perpetual Trading Signal Bot and LLM Research Bot, a zkSync-based yield protocol, and a Uniswap V3 simulator.
The latest AI product, Bella Signal Bot, is an AI-driven trading assistant that empowers users with real-time market insights, offering long, short, and close signals based on advanced AI models. By integrating directly with Telegram, traders can seamlessly receive alerts for their preferred token pairs and execute informed trades with ease, helping them stay ahead of market movements.
The Bella Research Bot, delivered via Telegram, is an advanced AI solution powered by LLM technology and optimized for Retrieval-Augmented Generation (RAG). It excels in text search and delivers real-time, trading-related data seamlessly.
The flagship product, Bella LP Farm, is a yield protocol based on zkSync Era, Mantle Network, and Manta Pacific that optimizes returns on liquidity provision. By staking LP tokens on an intuitive portal, users can effortlessly bolster potential earnings with multiple token rewards.
Bella Protocol caters to the needs of developers and quant strategists with a unique offering called Tuner. This programmatic Uniswap V3 simulator enables users to backtest and fine-tune their quantitative strategies on a transaction-to-transaction basis. With the ability to work with arbitrary or historical data without relying on the EVM, Tuner operates independently while fully preserving the exact smart-contract behavior of the intricate design and implementation of Uniswap V3.
Bella Protocol is backed by Binance Labs, Arrington XRP Capital, and several other renowned investors.
For more information about Bella or to join our team, please contact us at contact@bella.fi
Learn about Bella’s recent official news：
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