Uploaded October 2025 | Updated September 2026, 2 weeks ago
🚀 Building Scalable Agentic Applications with FloTorch #agenticai #scalableai #flotorch
As enterprises move beyond simple prompts into complex, autonomous workflows, the challenge lies in seamlessly integrating LLMs, external tools, and memory into reliable, production-grade AI systems.
In this session, Anjaneyalu T (AJ), Director of Data Science at FloTorch, will share best practices for designing robust Agentic Applications at scale. You’ll learn how to:
✅ Integrate multiple LLMs, memory stores, and tools into unified workflows
✅ Implement observability with Traces & OpenTelemetry for monitoring and debugging
✅ Build reliable, multi-step agentic workflows for enterprise use cases
✅ Ensure safety, governance, and performance in production environments
A live demo will walk you through building a scalable agent with FloTorch - from adding memory and tool-use logic to embedding observability into pipelines.
---------
⏱️ Timestamps
00:00 – Intro & Speaker
01:00 – Recap of Part 1
03:00 – What Are AI Agents?
05:00 – Agents vs Chatbots
07:00 – Key Components of Agents
09:00 – Types of Agents
11:00 – Building Scalable Agents
13:00 – Why Use FloTorch
15:00 – Demo 1: Local Tool Agent
21:00 – Demo 2: RAG Agent
28:00 – Demo 3: MCP Agent
35:00 – FloTorch Access & Wrap-Up
---------
👉 Learn more about Data Science Dojo:
datasciencedojo.com
👉 Explore video tutorials:
datasciencedojo.com/tutorials
👉 See community feedback and success stories:
https://datasciencedojo.com/data-scie...
At Data Science Dojo, we believe data science is for everyone. Our in-person and virtual training programs have helped 10,000+ professionals from 2,500+ companies — including Microsoft, Apple, and Meta — apply AI responsibly and effectively.
🔗 Subscribe to our newsletter for more AI tutorials and events:
datasciencedojo.com/newsletter
🚀 Building Scalable Agentic Applications with FloTorch #agenticai #scalableai #flotorch
As enterprises move beyond simple prompts into complex, autonomous workflows, the challenge lies in seamlessly integrating LLMs, external tools, and memory into reliable, production-grade AI systems.
In this session, Anjaneyalu T (AJ), Director of Data Science at FloTorch, will share best practices for designing robust Agentic Applications at scale. You’ll learn how to:
✅ Integrate multiple LLMs, memory stores, and tools into unified workflows
✅ Implement observability with Traces & OpenTelemetry for monitoring and debugging
✅ Build reliable, multi-step agentic workflows for enterprise use cases
✅ Ensure safety, governance, and performance in production environments
A live demo will walk you through building a scalable agent with FloTorch - from adding memory and tool-use logic to embedding observability into pipelines.
---------
⏱️ Timestamps
00:00 – Intro & Speaker
01:00 – Recap of Part 1
03:00 – What Are AI Agents?
05:00 – Agents vs Chatbots
07:00 – Key Components of Agents
09:00 – Types of Agents
11:00 – Building Scalable Agents
13:00 – Why Use FloTorch
15:00 – Demo 1: Local Tool Agent
21:00 – Demo 2: RAG Agent
28:00 – Demo 3: MCP Agent
35:00 – FloTorch Access & Wrap-Up
---------
👉 Learn more about Data Science Dojo:
datasciencedojo.com
👉 Explore video tutorials:
datasciencedojo.com/tutorials
👉 See community feedback and success stories:
https://datasciencedojo.com/data-scie...
At Data Science Dojo, we believe data science is for everyone. Our in-person and virtual training programs have helped 10,000+ professionals from 2,500+ companies — including Microsoft, Apple, and Meta — apply AI responsibly and effectively.
🔗 Subscribe to our newsletter for more AI tutorials and events:
datasciencedojo.com/newsletter
