Workflows for work that runs the business

Today, we're releasing Workflows in public preview. Workflows is the orchestration layer for enterprise AI. It brings the durability, observability, and fault tolerance required to move AI-powered processes from proof of concept to production reliably. Organizations like ASML, ABANCA, CMA-CGM, France Travail, La Banque Postale, Moeve, and many more are already running Workflows to automate critical processes.

Enterprise teams today have access to capable models. What they lack is a way to run them reliably in production. We see this across every industry we work with. The failure modes are consistent: pipelines that run in a notebook but fail silently in production with no trace, long-running processes that can't survive a network timeout, multi-step operations that need human approval mid-execution but have no mechanism to pause and resume, and systems that offer no way to verify they're still doing what they're supposed to after deployment. 

Building all of the capabilities to address these challenges is months of complex work for enterprises: the orchestration layer has to be stitched together from scratch, and the components it connects, inference, agents, connectors, observability, each come from different tools with their own interfaces and formats. 

Workflows is part of Studio, so the orchestration layer and the components it orchestrates are built to work together. Once a business process is identified, developers write the workflow in Python. Every workflow can then be published to Le Chat so anyone in the organisation can trigger it. Every step is tracked and auditable in Studio. By bringing all of this together, Workflows lets your organisation go from identifying a use case to running it in production in days. 

As mentioned, Mistral AI customers are already using Workflows to automate business processes and run them in production. The examples below show how durability, observability, and human-in-the-loop approvals work in practice.