Case Study: Lindy boosts reliability and observability of AI agents with Temporal Cloud

Lindy boosts reliability and observability of AI agents with Temporal Cloud

Lindy, an AI agent orchestration platform, needed a more reliable way to run complex, long-running workflows with deep third-party integrations. Before adopting Temporal Technologies, the team relied on BullMQ and in-house fixes, but execution failures, timeouts, and infrastructure issues led to silent failures and reduced customer trust.

Using Temporal Cloud from Temporal Technologies, Lindy modeled each agent wake-up, API call, and LLM interaction as a Temporal Workflow to improve durability, retries, and observability. The result was a more reliable and scalable platform with 2.5 million Temporal actions processed daily, better visibility into execution paths, fewer silent failures, and stronger customer trust.

Lindy

Luiz Scheidegger

Head of Engineering