Get insights and learn lessons on building an in-house, proprietary multi-agentic conversational workflow for the enterprise. Hear about its journey to create a state of the art and proprietary multi-agentic AI workflow that meets the needs of various users. Best practices, approaches and learnings from real-world experiments and applications for building an agentic workflow with several local agents that understand natural language prompts, create an action plan, validate the plan and explain it back to the user before taking action on their behalf will be discussed. Key takeaways: → Hear insights on how Capital One built an in-house multi agentic conversational AI workflow → Learn how the team overcame the challenge of designing a conversational workflow that understands user needs and can build a plan with a combination of actions to meet those needs while maintaining specific business constraints → Get best practices for incorporating risk mitigation and human-in-the-loop processes into conversational generative AI workflows in the enterprise.