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Building Custom Reasoning Models to Achieve Advanced Agentic AI Autonomy

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Home Β» How to Build an Agentic AI System Using the Best Tools and Frameworks

How to Build an Agentic AI System Using the Best Tools and Frameworks

NVIDIA News by NVIDIA News
March 7, 2025
in Apps, Computers, Generative AI, How To, News
Reading Time: 3 mins read
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Session ID: S73739

🎀 Speakers:

  • Bartley Richardson | Director of Engineering, NVIDIA
  • Kris Murphy | Technical Product Manager, NVIDIA

πŸ“… Date & Time: Wednesday, March 19 | 12:00 AM – 12:40 AM EAT


Introduction: The Rise of Agentic AI Systems

AI agents are the next evolution of digital intelligence, capable of:
βœ… Understanding complex tasks and reasoning about a mission
βœ… Planning multi-step workflows autonomously
βœ… Retrieving and processing data efficiently
βœ… Using tools and APIs to generate high-quality responses

However, enterprise-scale data presents a challengeβ€”the sheer magnitude and complexity make it difficult and costly to utilize effectively.

πŸ” Solution: This session will explore the best tools and frameworks for building agentic AI systems that:

  • Connect AI agents to reusable tools
  • Unlock enterprise data efficiently
  • Drive automation and efficiency across industries

Key Components of an Agentic AI System

1. AI Agents & Reasoning Capabilities

πŸ”Ή Multi-Step Reasoning – AI agents must break down missions into logical steps.
πŸ”Ή Autonomous Planning – Agents should be able to create and adjust plans dynamically.
πŸ”Ή Self-Learning & Adaptation – AI should improve over time using reinforcement learning (RLHF).

2. Tools & Frameworks for AI Agents

βœ… NVIDIA NeMo – Advanced LLM development & fine-tuning
βœ… Retrieval-Augmented Generation (RAG) – Enhancing AI with external knowledge
βœ… APIs & Integrations – Connecting agents with enterprise data
βœ… Reinforcement Learning (RLHF) – Improving agent performance through feedback-based learning

3. Enterprise Data Utilization

πŸ“Œ Data is the foundation of AIβ€”but enterprise data is often siloed, unstructured, and costly to process.
πŸ“Œ Agentic AI systems must unlock value from enterprise data while optimizing efficiency and reducing costs.


Real-World Applications of Agentic AI

🏦 Finance – AI agents analyze market trends and provide automated trading insights.
πŸ₯ Healthcare – AI agents assist in medical diagnosis and patient data retrieval.
πŸ“¦ Supply Chain & Logistics – Agents optimize inventory management and predict demand fluctuations.
πŸ“ž Customer Support – AI-powered agents handle complex customer queries with personalized interactions.


Why Attend This Session?

πŸš€ Learn how to build intelligent AI agents that think, plan, and execute tasks autonomously.
πŸ”§ Explore cutting-edge frameworks like NVIDIA NeMo, RAG, and RLHF.
πŸ“Š Understand how AI agents can transform enterprise workflows by unlocking the power of data.

πŸ”— Join us to discover how AI agents will shape the future of business automation! πŸš€

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