Case Study: Sunrun achieves reliable, scalable AI operations with Helicone

Sunrun cuts LLM errors and speeds debugging with Helicone

Sunrun, America's leading residential solar company, faced a challenge in scaling its AI operations, which relied heavily on LLMs. Their team needed infrastructure with built-in caching and critical visibility into their AI operations to quickly react to issues. They adopted Helicone's observability and monitoring platform from the very beginning of their AI journey to address these needs.

By implementing Helicone, Sunrun gained built-in caching, real-time alerts, and property-based analytics without any setup overhead. The solution provided instant issue detection during provider outages and revealed performance bottlenecks through latency optimization. This allowed Sunrun's engineering team to focus on building features instead of maintaining custom infrastructure, establishing a foundation of observability and reliability for their AI-powered operations.

Sunrun