Mistral Workflows is an orchestration platform for building, executing, and monitoring complex AI-driven workflows. It provides durable, fault-tolerant workflow execution backed by battle-tested distributed systems infrastructure, combined with a developer-friendly SDK optimized for Mistral's AI services.

Workflows addresses the complexity of building, managing, and scaling multi-step AI processes reliably. It provides a structured environment for defining, executing, and monitoring workflows — from simple sequences to complex, stateful processes — ensuring completion even with transient failures.

Reliable execution. Workflows never lose their place. Every step is persisted before the next begins, so failures — process crashes, network drops, transient errors — are handled automatically without any recovery code on your part. This is powered by Temporal, the industry-standard engine for durable workflow orchestration.

Built for agentic applications. Workflows is designed for AI-native use cases: multi-step agents, tool-calling loops, model chains, and long-running assistant interactions. The SDK integrates natively with Mistral's models and services, and workflows can run for seconds or weeks without losing state.

Observable by design. Every action inside a workflow — activity completions, signals received, errors encountered — is recorded as a real-time event. These events can be streamed to external systems, making it straightforward to build live progress UIs, trace agent behavior, or power observability dashboards without polling.

Simple to build. The Python SDK uses decorators and familiar async patterns. Getting from an idea to a running workflow takes minutes, not days.

Modern AI applications involve multi-step processes that are complex to build reliably. Integrating services, handling retries, ensuring observability, and managing long-running tasks quickly becomes an engineering challenge. Workflows provides the infrastructure to focus on your AI workflow logic rather than orchestration complexity.