The operating system
for your processes

ProcessOS is the intelligence layer of the Camunda platform: an AI system that re-engineers business processes for an AI-native world. It uses four specialized agents to discover how your processes actually run, design what they should become, build and deploy them, and continuously improve them in production. It is not a modeling tool or a monitoring dashboard. It is the layer that makes process transformation fast, repeatable, and self-improving.

Adding AI to a legacy process speeds up individual steps, but the process was designed around human limitations and those constraints stay. Re-engineering means starting from the outcome you want and designing a process that uses AI natively from the ground up. The results are qualitatively different. Danica re-engineered their customer onboarding with Camunda: a process that took months now takes days. That kind of result is not achievable through optimization alone.

Process mining discovers what is happening in your operations. ProcessOS discovers what is happening and then acts on it, re-engineering the process around the outcomes you want to achieve, building it, deploying it, and improving it continuously. ProcessOS can use process mining tools like Celonis or MPMX as plugins to enrich the discovery phase, making sure you can leverage all your existing process intelligence investments.

There are three modes. First, you can direct the ProcessOS agents directly through the UI, reviewing outputs, approving designs, redirecting the agents as they work. Second, you can use ProcessOS Agent Skills as a plugin in your own coding agent (such as Claude Code), accessing the full range of discovery, design, build, and optimize operations from your own toolchain. Third, you can work manually in the Workspace, using Web Modeler and the Catalog. All three modes write to the same Project Repository.

When you define an outcome goal in ProcessOS, you configure a fitness function: a weighted scoring model across KPIs such as cycle time, resolution rate, cost per case, and compliance rate. ProcessOS uses this function to score process variants during design and to evaluate every proposed improvement before it reaches production. You set the weights based on what matters most in your domain.

ProcessOS monitors live process performance against your fitness function. When it identifies a potential improvement, it backtests that change against your historical process data (real cases, real edge cases, real outcomes) and models the projected impact on your score before surfacing a proposal. You review the evidence and approve the change. Nothing reaches production without human sign-off.

Organizational memory is a knowledge model that ProcessOS builds as it operates in your environment: your systems, integration patterns, operational edge cases, and process decisions. It lives in a git repository private to your organization and is never used to train shared models. Combined with the Catalog of proven connectors and building blocks, it means every process you build makes the next one faster. The tenth process is dramatically faster than the first. Not because the tool improved, but because it knows your business.

Process Zero is how you start. A team of Camunda Forward Deployed Engineers embeds with your organization, defines a measurable outcome goal with you, and delivers your first production-grade process end-to-end, using ProcessOS throughout. By the time the engagement completes, you have a running process, organizational memory seeded from real operations, and an internal team ready to operate and extend independently.

ProcessOS is currently in closed beta. We are running a limited number of Process Zero engagements during the pilot phase. Sign up to be notified when access opens and to discuss whether your organization is a good fit.