Discover how Elixir’s concurrency model enables building autonomous AI sales agents that manage over 200 million leads while processing millions of buying signals in real-time. This talk reveals the architecture behind Nexuscale.ai - a B2B sales platform where AI agents automatically identify high-intent prospects and generate personalized outreach at scale.
We’ll explore practical patterns for integrating AI models with Elixir, handling massive datasets, and orchestrating complex AI workflows using GenServers and OTP supervision trees. Learn how we built fault-tolerant systems that scan 2.4M+ data points daily, achieve 94% targeting accuracy, and deliver 3.2x higher conversion rates.
Key technical insights include: real-time signal detection, AI model integration strategies, concurrent data processing, and building resilient AI agents that never miss opportunities. Perfect for developers building AI-powered applications who need proven patterns for scale and reliability.
Key Takeaways:
- This talk aims to bridge the gap between AI/ML theory and production-ready Elixir applications by sharing battle-tested patterns from managing 200M+ leads in a live B2B sales platform. Attendees will leave with concrete architectural knowledge, specific code patterns, and confidence to build their own scalable AI-powered systems using Elixir’s unique strengths in concurrency and fault tolerance.
Target Audience:
- Elixir developers looking to integrate AI capabilities into their applications, backend engineers evaluating Elixir for data-intensive projects, and technical leads responsible for building scalable automation systems. Also valuable for developers from other languages curious about Elixir’s advantages in AI/ML workflows and anyone building B2B tools that need real-time data processing at scale.