< session />
Building Hierarchical Multi-Agent RAG Systems
Wed, 23 April
As Agentic AI systems become more complex, hierarchical multi-agent architectures offer a scalable and modular approach to automation. By breaking down tasks into specialized agents, organizations can achieve greater efficiency, adaptability, and composability in AI-driven workflows.
This session explores the design and implementation of hierarchical AI agents for Retrieval-Augmented Generation (RAG) systems. We will introduce specialist agents that focus on specific tasks and an Orchestrator agent that dynamically selects and coordinates the right specialist agents based on the customer journey.
Through practical examples, we’ll discuss how to structure multi-agent systems for various applications, such as AI-powered customer support, document processing, and workflow automation. Attendees will gain hands-on knowledge about the advantages, architecture, and deployment of hierarchical agent-based systems.
Key Takeaways
- Advantages of hierarchical multi-agent systems – Why modular and composable agents improve automation.
- Building specialized AI agents – How to design task-specific AI models for retrieval, generation, and decision-making.
- Orchestrator agents for dynamic task execution – Using AI to select and coordinate specialist agents based on the customer journey.
- Deploying hierarchical multi-agent RAG – Best practices for integrating AI agents into real-world enterprise workflows.
- Scaling AI-powered automation – How hierarchical multi-agent designs enhance efficiency, accuracy, and maintainability.
Target Audience
- AI Engineers & Machine Learning Practitioners building multi-agent architectures.
- Software Architects & Developers integrating AI-driven RAG workflows into applications.
- Enterprise AI & Automation Teams looking to enhance customer interactions using intelligent multi-agent systems.
- Product & Innovation Leaders exploring AI’s role in automating complex business processes.
By adopting hierarchical multi-agent RAG architectures, enterprises can build scalable, intelligent AI workflows that automate or assist in multi-step customer journeys. This session will equip attendees with the knowledge to design, deploy, and optimize multi-agent AI solutions, paving the way for more efficient and adaptable automation systems.
< speaker_info />
About the speaker
Raghavan Narasimhan
Lead Enterprise Architect, Lloyds Technology Centre
Raghavan has over 20 years of experience in the software industry, working with a diverse range of clients, including Target, Ascena Retail, Kohl's, and ASDA. His professional journey spans a broad skill set, from architecture assessment and roadmap creation to solution design and hands-on development.
He is passionate about leveraging new tools and technologies, with a strong focus on open source, Cloud DevOps, and cloud-native microservices. His expertise lies in transforming monolithic applications into microservices, ensuring scalable and efficient solutions that align with modern engineering standards.
Driven by a continuous pursuit of technological advancement, Raghavan is committed to enhancing processes and delivering high-quality software solutions. He actively seeks new learning opportunities, books, and technologies to drive innovation and improve engineering practices.
