Camunda Writes New Score For Agentic AI Orchestration

As smart AI begins to be integrated into all levels of enterprise software platforms and applications (we must emphasize that there are both powerful core tools and some less reliable simulation tools), we need a new set of infrastructure capabilities to manage these agents.

Camunda, a process orchestration company based in Berlin, Germany, believes it can help smart AI play its due role and align with accurate business goals and rules in the new digital workplace. The company currently offers intelligent orchestration capabilities designed to help organizations model, deploy and manage AI agents.

From a practical software engineering perspective, what does this mean?

The integration of certainty and non-deterministic processes

The key is to allow users, often data scientists, software developers and AI engineers, to create a harmonious fusion of “deterministic orchestration” and “non-deterministic orchestration.” "Deterministic orchestration" is achieved through standardized business process models and conceptual technologies (taking action to drive AI tools to achieve established goals, data loads, and information endpoints); while "Nondeterministic orchestration" is cleverly integrated into the use of AI agents (which will solve problems based on the datasets, pattern recognition opportunities, models, and inference engines we provide), allowing software and business teams to implement as much or as little AI as needed within the guardrail.

Camunda further defines the specific meaning of applying deterministic non-deterministic methods to process execution.

This technology is designed to provide intelligent process orchestration capabilities, enabling organizations to operate and control AI by converging deterministic process execution (driven by design-time logic defined) and non-deterministic process execution (driven by runtime logic determined by runtime using AI models and runtime data). This balance is designed to achieve the necessary compliance and standardization. It also has the ability to introduce resilient AI-enhanced personalization and adaptability.

In addition to its intelligent orchestration capabilities, Camunda now introduces AI-enhanced capabilities for its so-called dynamic, intelligent decision making and process generation.

“To unlock the full potential of AI, organizations must go beyond siloed applications and run AI in a holistic, composable enterprise architecture … This architecture seamlessly integrates AI with people, systems and devices,” said Daniel Meyer, CTO of Camunda. “Our new intelligent process orchestration capabilities provide the control and transparency required for compliance, while leveraging AI-driven decision-making to enhance automation, optimize operations and efficiently scale business processes.”

According to Camunda's 2025 Process Orchestration and Automation Status Report, 84% of IT and business leaders hope to add more AI capabilities over the next three years. This is obviously neither an accident nor a new discovery, and similar estimates abound; interestingly (whether that number is 66%, 84%, or 93.5%), how organizations trying to graft intelligent AI into their business processes will be able to scale and run AI in their business.

Design-time and run-time logic

The latest Camunda version includes some other AI-enhanced features and task automation capabilities. Temporary subprocesses enable tasks to be activated dynamically without predefined task order. By using the above business process models and notation methods ( BPMNs well known in this technical field), temporary subprocesses, AI agents can autonomously manage tasks within the scope of definition, execute them in any order, repeat steps as needed, or skip them according to changing real-time conditions.

Camunda's built-in support for temporary subprocesses and AI connectors means organizations can experiment and integrate AI into their processes with more confidence, reducing risk.

Camunda Copilot allows users to generate BPMN graphs from any text input, whether in simple natural language or legacy code, or to generate documents or suggestions from existing graphs. By using chat capabilities, technology and business users can ask follow-up questions, test cases and iterate to scale and enhance processes to meet business needs and ensure certain steps occur. This saves time, reduces manual work, and improves the quality of the process model.

Camunda Robot Process Automation Technology is designed to enable users to integrate and bridge legacy systems without application programming interfaces, create and orchestrate robots, elevating siloed task automation to scalable end-to-end process orchestration to fully run AI across all people, systems and devices.

Camunda Intelligent Document Processing allows users to convert documents into data using AI-driven document processing, providing the flexibility to select any large (or small) language model and then customize and extend the software. It can convert non-machine-readable documents into structured data, enabling them to be used for AI-driven automation and decision-making.

According to CTO Meyer, Camunda SAP integration allows users to modernize their ERP environments, confidently migrate to S4/HANA, and introduce AI and automation through end-to-end orchestration to truly fully run AI across all people, systems and devices (including ERP); Camunda SAP integration is the first of a series of “systems of record” integrations.

Orchestrating the "Symphony" of AI

Camunda is clearly working to orchestrate AI and automation through technologies designed to bring harmony to possible noises (this is the last music term, we guarantee), software tools, AI agents, APIs and other connections all produce white noise.

Because interrupted and disconnected business processes can annoy users (your bank credit card approval is basically handled by the machine, if your mailing address doesn't match the previous record, even if you have updated it in your bank application but not in your branch, you may be rejected…etc.), it is clear that a highly scalable orchestration layer process is needed that works with real-time data and is able to support high transaction volumes and personalized customer experiences. That's what Camunda did.

The name Camunda may have been derived from the Latin verbs “capere” (understand) and “munda” (clean), so let us hope that future AI agents can operate in a terra mundata (clean world).

The above is the detailed content of Camunda Writes New Score For Agentic AI Orchestration. For more information, please follow other related articles on the PHP Chinese website!