Lindy boosts reliability and observability of AI agents with Temporal Cloud

Lindy is an AI agent orchestration platform designed to help businesses create, manage and share agents. Customers use Lindy to handle tasks across sales, support, operations, and executive workflows, such as meeting scheduling, outreach automation, and knowledge management.

To power these advanced agent-based experiences, Lindy needed a reliable execution layer that could support long-running, complex workflows with deep third-party integrations.

The challenge

Before adopting Temporal, Lindy’s engineers relied on a queue-based system (BullMQ) and various in-house fixes to manage background work. But this stack lacked durability and consistency. With third-party APIs prone to timeouts or outages, and infrastructure challenges like pod shutdowns, Lindy agents would often fail silently or unpredictably. The result: missed automations and reduced customer trust.

Why Temporal

Lindy chose Temporal Cloud after considering options like PubSub, Kafka, and Airflow. Temporal’s open-source foundation, strong task observability, and production-grade durability made it stand out.

“We heard great things from other teams,” said Scheidegger. “We needed something developer-friendly and operationally efficient, and Temporal was it.”

Because Lindy is a lean team, they opted for Temporal Cloud to avoid the overhead of managing their own deployment.

The solution

Lindy uses Temporal to orchestrate the core execution of its AI agents. Each agent wake-up, API call, or LLM interaction is modeled as a Temporal Workflow. This approach gives engineers fine-grained control over failures, retries, and time-based triggers.

With Temporal:

• Workflows span LLM calls, API integrations, and internal systems
• Agents are fully observable and recoverable

"Without Temporal, our agents would be fragile. Now, we have the primitives and visibility to build robust automation," Scheidegger noted.

Results

Adopting Temporal has made Lindy’s AI platform more reliable and scalable, unlocking measurable improvements:

• 2.5M Temporal actions processed daily
• Better visibility into agent execution paths
• Fewer silent failures and more recoverable automations
• Stronger customer trust and improved platform perception

As Lindy continues to grow, Temporal provides the foundation to confidently scale agent behavior across new domains and use cases.