Building an Advanced LLM Agent Platform with Elixir

A Deep Dive into Real-Time Chat and Flow Logic

At FoundYou, we specialize in building scalable and efficient systems, and one of our recent projects involved creating an LLM-based agent platform. This product needed to support real-time events, chat streaming, and complex flow logic—all tasks that Elixir and the BEAM were designed to handle exceptionally well.

In this post, we’ll dive into how Elixir, paired with Phoenix Channels and Phoenix LiveView, enabled us to implement a powerful real-time chat system, and we’ll also take a look at how other platforms like WhatsApp and Discord have leveraged BEAM languages for similar use cases.

Elixir and Phoenix: Real-Time Communication Made Simple

For this platform, real-time interaction between users and LLM agents was a core feature. The challenge was to ensure seamless communication where users could interact in real time, and messages would be processed and broadcasted without any lag.

Using Phoenix Channels, we were able to establish WebSocket connections that allowed real-time message transmission between clients and the server. As users sent messages, the Phoenix Channel server broadcasted them instantly to all connected users, maintaining a fluid conversation flow.

Take a look at this diagram to better understand how real-time chat with Phoenix Channels works:

In this system:

Client: Multiple clients (browsers) connect to the server through WebSockets.
Server: Phoenix Channels handles the WebSocket connections, enabling real-time message broadcasting.
Broadcasting: Messages from one client are instantly broadcasted to all other connected clients, ensuring a dynamic real-time experience.

Why Phoenix LiveView for Real-Time Updates?

While Phoenix Channels is excellent for real-time chat, we also used Phoenix LiveView for dynamic updates on the user interface. LiveView allows us to create interactive applications where changes on the server side can immediately reflect on the client without needing a full page refresh.

For example, in the LLM platform, whenever the agent provided new responses or the user’s flow logic changed, LiveView enabled the platform to update the conversation UI dynamically. This made the user experience more fluid and responsive, enhancing interaction with the LLM.

Learning from WhatsApp and Discord

Two of the most well-known real-time chat platforms, WhatsApp and Discord, were built using BEAM languages like Erlang and Elixir. They provide excellent examples of how these technologies handle high concurrency, fault tolerance, and low-latency communications—just like the platform we built.

WhatsApp: With over 2 billion active users, WhatsApp relies on Erlang and the BEAM for its messaging infrastructure. The ability of BEAM to handle millions of concurrent connections allows WhatsApp to process billions of messages daily without performance bottlenecks.
Discord: Discord adopted Elixir to power its real-time messaging system, where millions of users engage in voice, video, and text chats. Elixir’s lightweight processes and fault tolerance enable Discord to maintain a highly interactive, low-latency system while handling a large user base.

By learning from these examples, we applied similar principles when building the LLM platform’s real-time chat and event-driven systems, ensuring that it could scale seamlessly and deliver a reliable, high-performance user experience.

Why Elixir Was the Perfect Fit

Elixir’s concurrency model and the BEAM’s fault-tolerant design provided the perfect framework for handling complex, real-time communication and event-driven systems. Here’s why it was ideal for this project:

Concurrency at Scale: The platform required managing thousands of simultaneous chat streams. Elixir’s lightweight processes made it possible to handle this concurrency efficiently.
Fault Tolerance: In any real-time system, failures are inevitable. However, the BEAM’s ability to isolate and recover from failures without crashing the system ensured that users experienced minimal disruptions.
Scalability: With Phoenix and Elixir, scaling the system horizontally to handle more users was straightforward, allowing us to grow the platform as demand increased.

At FoundYou, we are excited to leverage these technologies to build powerful, scalable solutions for our clients. Whether it’s real-time chat, complex flow logic, or data streaming, Elixir and Phoenix provide the tools we need to create cutting-edge systems that deliver outstanding performance.