Case Study: Snorkel AI achieves 20x faster LLM prompting and reliable workflow execution with Prefect Open Source

Snorkel AI boosts LLM prompting throughput 20x with Prefect

Snorkel AI, a company that builds the data layer for specialized AI, faced significant challenges with their custom workflow orchestration system. As their machine learning workloads grew more complex, their initial solution using Redis Queue became inefficient, lacking proper resource isolation, observability, and scalability. This led to performance bottlenecks and required the team to build and maintain extensive custom tooling for caching, telemetry, and dependency management.

By implementing Prefect Open Source, Snorkel AI was able to incrementally migrate their workflows to a more robust platform. Prefect provided the necessary orchestration, resiliency with retries, and incremental processing capabilities. The solution delivered a 20x performance improvement in LLM prompting job throughput and reliably executes tens of thousands of workflows daily, all while eliminating technical debt by replacing their homegrown systems.

Snorkel AI