Contact centers powered by multi-agent AI systems represent a step change in customer engagement. Unlike traditional software that follows rigid, predefined rules, agentic AI systems operate with autonomy, enabling them to independently achieve goals. In this webinar, we explain how to build and monitor multi-agent AI contact centers with Weights & Biases. We’ll dive into agent tracing, quality assessment, and achieving consistent support across multiple communication channels. Then hear from Telnyx. They will share real-world insights from launching thousands of agents supported by Rime’s leading voice models.
What to expect
What it takes to build reliable AI agents end-to-end
How teams can visualize and debug multi-modal agents
Exploration of new fine-tuning techniques, such as reinforcement learning (RL), that allow you to post-train LLMs for multi-turn agentic tasks to improve reliability, speed, and costs
An overview of inference strategies and tradeoffs, including practical approaches to managing cost per token
What you’ll learn
How to support the full agent building workflow from exploration to prototype to fine-tuning and deployment
Tips to get started, including sample architectures
Who should attend
AI researchers, AI engineers, software developers, and AI leaders
Webinar
