Inside the engine: Xautomata’s orchestration engine 

In the industrial automation landscape, the shift from simple data collection to proactive asset management represents the real technological challenge.

For Xautomata, this implies more than just describing how to execute a sequence of tasks; it means managing dynamic complexity in real-time. The core of our product, Xautomata, is an automation engine designed to transform operational uncertainty into resilient, efficient, and scalable deterministic flows.

The architecture: collaborative agents 

 At the center of Xautomata’s architecture lies the proprietary modeling language XAL (eXtended Automata Language). Unlike rigid automation systems, this model is built on a system of agents that enables the definition of complex Behavioural Models.

In Xautomata, therefore, every process is a living entity.

Our collaborative agents represent a Process Digital Twin (DTO)—an always up-to-date virtual representation that allows for precise analysis, simulation, and intervention in the event of anomalies.

Our key strength lies in the engine’s capability to instantiate specific processes in real-time, enabling the application of deterministic behavioral models. These models communicate with one another to synchronize their states, thereby defining a complex system that evolves based on a holistic vision of business rules.

Xautomata and Agentic AI: the value of determinism 

Recently, the adoption of Agentic AI systems has opened new frontiers, but it has also highlighted some critical limitations of the technology. These systems use an LLM as a reasoning engine to plan and execute complex tasks.

However, their innate probabilistic nature necessitates supervision.

In this landscape, Xautomata stands out by offering deterministic governance through:

• Reliability and determinism: every logic and automation is defined by clear, traceable, and deterministic behavioral models, free from the hallucinations that are still inevitable when using LLMs.
• Costs and scalability: The combination of deterministic and on-demand process logics allows for limiting the use of expensive inference resources.
• Governance: Thanks to the definition of behavioral rules, it is possible to certify process decision-making logics.

Ultimately, the Xautomata engine does not replace other technologies but acts as an intelligent centralizer. It is capable of dynamically selecting and coordinating the most suitable technologies for each phase of the process, integrating various traditional technology stacks (RPA, IoT, etc.) with AI and LLM systems within a unified control layer.

Scalability and infrastructural stack 

To guarantee the performance required by mission-critical applications, Xautomata’s technology stack is designed to offer robustness and scalability. The architecture is built upon market-leading components:

• Kubernetes for container and microservices orchestration,
• Kafka for real-time event stream management,
• Spark for distributed and scalable data processing.

In conclusion, the Xautomata engine does not simply monitor: it orchestrates, predicts, and guides human and technological intervention, freeing experts from repetitive tasks and allowing them to focus on resolving complex problems and driving strategic improvements.