Pundi AI Empowers AI Trading Bot Development Via Bella Protocol's Advanced Signals

Pundi AI recently bridged capabilities with Bella Protocol to unlock sophisticated AI-driven trading and research tools for the decentralized ecosystem. This strategic partnership fuses Bella’s market intelligence platform with Pundi AI’s decentralized data backbone, creating a robust foundation for AI agents to thrive in Web3 environments. The collaboration equips developers and trading bot creators with enterprise-grade resources previously limited to centralized platforms.

Real-Time Signals Fuel Intelligent Bot Strategy

The core of this integration centers on Pundi AI’s access to Bella’s Signal Bot API, which streams perpetual trading signals across token pairs with precise long, short, and close indicators. Developers building next-generation AI trading bots can now integrate these signals directly into their applications, enabling real-time market analysis and automated strategy execution. This capability transforms how decentralized trading bots navigate volatile markets—moving from reactive to predictive intelligence. Token pair analysis, market sentiment indicators, and signal verification can now operate seamlessly within the AI bot ecosystem, giving traders and builders a competitive edge in on-chain markets.

Telegram Integration Brings Research to Your Fingertips

Beyond trading signals, Bella’s Research Bot—a large language model-powered Telegram assistant—now surfaces Pundi AI ecosystem data, product roadmaps, and activity updates directly to users. This integration eliminates information silos and creates a more transparent, user-friendly experience. Community members can instantly access ecosystem insights, reducing friction between protocol updates and market awareness.

Strengthening Web3’s AI Infrastructure Layer

This partnership exemplifies why decentralized data infrastructure matters. By combining Bella’s signal generation with Pundi AI’s transparent on-chain data layer, both projects reinforce the foundation for open, verifiable AI applications. Rather than trusting black-box trading algorithms, developers can now build systems anchored in transparent, accessible data sources. Both teams signal intentions to expand integrations further, positioning this as a launchpad for broader AI agent adoption across Web3. The message is clear: the future of decentralized trading depends on robust infrastructure that connects AI capability with verifiable, decentralized data.