At CamundaCon 2026, in front of 1,200 enterprise leaders and technologists from 25 countries, Camunda unveiled ProcessOS — a new intelligence layer built on top of its battle-tested agentic orchestration platform.

The pitch is simple but ambitious: instead of buying yet another point solution to automate a single process, businesses get an AI-powered operating system that discovers every process running in the organisation, re-engineers it for an AI-first world, and keeps optimising it automatically against real performance targets.

What ProcessOS Actually Does

ProcessOS wraps four connected activities into a continuous loop:

1. Discover — the system reads existing knowledge bases, operational data, and process documentation to map what’s actually happening inside a business, not what anyone thinks is happening.
2. Design — AI re-engineers those legacy processes based on defined outcomes, asking the question “if we were building this from scratch knowing what AI can do, how would it look?”
3. Build — the re-engineered workflows are deployed as agentic processes on Camunda’s orchestration platform, which already handles millions of concurrent workflow instances daily for some of the world’s largest enterprises.
4. Optimise — the system monitors KPIs and keeps adjusting in real time, rather than waiting for a quarterly review to notice something is broken.

Camunda is positioning ProcessOS as the infrastructure layer that sits underneath AI agents — the thing that keeps agents coordinated, auditable, and actually useful at scale.

Why This Matters Now

Most organisations are not short of AI pilots. They are short of AI that sticks. The gap between a working prototype and a reliable process running at enterprise scale has derailed more AI projects than any technology limitation.

Camunda’s argument is that agentic AI needs an operating system the same way a computer needs one: something to manage resources, coordinate activity, handle failures, and give humans visibility into what is running. ProcessOS is that layer.

The platform runs natively on AWS, with deep integration into Amazon Bedrock and Amazon Bedrock AgentCore for foundation models, agent memory, identity, and gateway services. That matters because it means businesses can connect ProcessOS to the AI infrastructure they are already building without adding another vendor to manage.

The Bigger Picture: “The Great Re-Engineering”

Camunda’s framing around “the great re-engineering” is worth taking seriously. The argument is that most business processes were designed around what humans can do and what software could automate five years ago. Neither of those constraints apply anymore. AI agents can operate continuously, handle ambiguity, coordinate across systems, and adapt — which means the processes themselves need to be redesigned from scratch, not just patched.

For businesses that have been running workflow automation in some form for years, this is a meaningful shift in thinking. It is not about adding an AI step to an existing process. It is about asking whether the process itself still makes sense.

ProcessOS is currently available in closed beta for selected enterprises. Organisations can register interest at camunda.com/process-os.

What This Means for Business

If you run operations, finance, or HR at scale, the practical implication of tools like ProcessOS is that process redesign no longer requires months of consulting work and a six-figure implementation project. An AI layer can surface what is inefficient, propose a better model, and deploy it — with humans approving changes at key decision points rather than rebuilding everything manually.

For IT and engineering teams, the integration with Amazon Bedrock signals something important: enterprise AI infrastructure is consolidating around a small number of cloud-native stacks. Organisations that have made decisions about their cloud AI platform in the past 12 months are the natural early adopters here.

For business leaders thinking about AI investment, Camunda’s approach highlights the difference between buying AI and building AI capacity. ProcessOS is a platform bet — one that pays off over time as more processes are discovered, re-engineered, and optimised, rather than delivering a defined ROI from a single use case.

Enterprise DNA works with businesses navigating exactly this kind of decision: where to start with AI agents, how to build governance and oversight, and how to connect the tooling choices to actual business outcomes. If your organisation is evaluating agentic platforms or trying to move from AI pilots to production systems, our advisory team can help you build the right foundation.