Intent Recognition

Intent recognition enables xFractal’s AI agents to accurately understand user goals and execute relevant actions. xFractal employs a multi-layered approach, combining symbolic action definitions, contextual awareness, and memory-augmented processing.

At its core, xFractal uses a hierarchical action structure, where each intent is mapped to a primary identifier and semantic variations, ensuring flexible interpretation across different linguistic expressions. A context-aware evaluation system enhances recognition by leveraging real-time conversational states and long-term memory retrieval through vector-based models.

xFractal’s intent pipeline integrates template-driven context building with platform-specific interaction managers, ensuring seamless recognition across multiple communication channels. A dynamic memory system tracks conversation history, trading strategies, and past decisions, allowing agents to adapt intent recognition based on both immediate inputs and long-term interaction patterns.

This architecture ensures precise, contextually relevant responses, optimizing trading execution, market analysis, and user interactions with adaptive intelligence.

To learn more about our prompt engineering, please visit:

Prompting guide