Roadmap
Roadmap of Infinity AI in phases
Last updated
Roadmap of Infinity AI in phases
Last updated
Phase 1: Rebranding & Core Platform Integration
Transition from 0xAISwap to InfinityAI with a fresh new identity.
Launch of the new Infinity AI website and social media channels for community engagement.
Release dApp on Conversational AI-driven trading, portfolio management.
Release Extensive Limit orders and smart slippage mechanisms and run inside dynamic thread pool environment.
Release Telegram mini apps for Infinity AI telegram bot with new models integration.
Release Multi-token swap dApp allowing users to trade multiple tokens in a single transaction.
Phase 2: Platform As AI Agent (PAAI)
POC - Showcase the capabilities of PAAI through a Proof-Of-Concept.
PAAI allows automation of trading strategies, DeFi interactions, and market analysis.
Create custom workflows for advanced use cases such as risk management and portfolio optimization.
No-code integration of PAAI agents into decentralized applications (dApps).
Developers can build and access InfinityAI APIs via AI agents for seamless project creation.
Phase 3: Zero-Code AI Agent Builder (ZCAI)
ZCAI empowers users to create custom AI agents without coding.
Drag-and-drop interface to design complex trading and automation workflows.
Pre-Built AI Modules Choose from a library of pre-configured, powerful AI modules from the Infinity suite.
Multi-Role AI Agents Create a single AI agent with multiple roles and use it in work flow.
Zero-Code API access to InfinityAI’s core functionalities for ease of use
Harvest Data – Pull historical and real-time market data using APIs.
Shape Insights – Use AI to detect patterns and generate synthetic data for low-volume assets.
Build Models –Develop machine learning models (e.g., neural networks, logistic regression, MCST) for baseline predictions.
Optimize – Backtest and refine with real-time data.
Deploy – Automate and launch Predictive Analyser
Ongoing platform enhancements driven by user feedback.
Regular updates to AI agents based on real-world usage and community input.
New features and tool optimizations based on user needs and market trends.
Active integration of suggested improvements for better user experience.
Development of advanced AI workflows to support emerging use cases