The evolution of AI systems at Manychat is driving a shift from simple, rule-based automation to complex, multi-agent architectures capable of solving real-world business challenges. This approach allows for more dynamic interactions, better understanding of user needs, and enhanced problem-solving abilities across multiple business scenarios. Bullet Points: - Transition from traditional dialogue automation to AI-driven automation with multi-agent systems. - Architecture of Manychat’s AI multi-agent system: how different agents collaborate and solve complex tasks. - The importance of multi-agent systems in addressing critical business challenges (e.g., lead generation, customer support, or e-commerce automation). - Examples of business outcomes and statistics, showcasing the positive impact (increased conversion rates, reduced operational costs, etc.).
Session 🗣 Advanced ⭐⭐⭐ Track: AI, ML, Bigdata, Python
AI Agents; Conversational AI; GenAI; Multi-agents