AI systems are usually complex: Python APIs, model servers, queues, multiple frontends, and way too many moving parts.
At CloudWalk, we took a different path. We built a full-stack AI system in Elixir that serves over 3 million customers—handling everything from LLM-based chat to GPU-powered image moderation, all in one cohesive codebase.
In this talk, I’ll show how Elixir helped us: • Build a production-ready chat agent with multi-agent orchestration • Run neural networks on GPUs directly from Elixir using Bumblebee • Deliver real-time insights via LiveView dashboards • Avoid the overhead of microservices while scaling reliably
If you’re wondering whether Elixir can power serious AI at scale—this is living proof.
Key Takeaways:
- You can build and scale real AI systems in Elixir—LLMs, image models, dashboards, and all
- Elixir’s concurrency model and GPU integration (via Nx + Bumblebee) unlock surprising power
- LiveView enables full-featured, real-time operator UIs without extra frontend stacks
- A single, unified codebase can replace the complexity of multiple Python services
- Elixir is not just web/backend—it’s production-grade AI at scale
Target Audience:
- Elixir developers curious about AI/ML applications
- Engineers building or scaling AI-powered features (chatbots, moderation, etc.)
- Tech leads exploring alternatives to Python-heavy AI stacks
- Anyone interested in running LLMs, neural networks, and dashboards in one unified system
- Builders who care about simplicity, performance, and observability in production