The automation of business processes is often considered useful if it is simple, fast, traceable and cost-efficient. Another key aspect is the freedom to choose what exactly should be automated without being limited by technical restrictions.

In the past, it was too often technological limitations that hindered many digitalization projects, stifling them in the pilot phase. The technology dictated what was possible instead of focusing on the process itself. In addition, the hurdles posed by the skills required for planning through to implementation were often difficult or even impossible to overcome for many. Many companies were only able to automate certain sections of their value chains because complicated interfaces, poor data quality, system weaknesses or incompatible data structures prevented end-to-end automation.

This is where Business Orchestration and Automation Technology (BOAT) comes into play. BOAT stands for a new approach that goes beyond traditional process automation. It combines business process logic, technological feasibility and intelligent context processing into a uniform approach. This allows the user to decide what is to be automated – the platform takes care of the rest.

From Selective Automation to Intelligent Control

Conventional automation solves individual tasks, such as filling out a form or transferring data to another system.

BOAT goes a significant step further: it connects people, systems and information within an overarching process logic. In practice, this means that the business logic is modeled centrally in process diagrams, decisions are documented in a traceable manner and modules with artificial intelligence (AI) provide support where knowledge of the context or understanding of language is required. This combination creates a controllable, verifiable and customizable framework that forms the basis for sustainable digital transformation. It is crucial that actions are normally predictable, or at least comprehensible and repeatable under the same conditions.

The goal is clear: to move away from isolated stand-alone solutions towards a centrally controlled company operation in which systems, data sources and employees work together smoothly.

The Levels of Orchestration: From Process to Intelligence

BOAT can be divided into different technical and functional levels:

1. process orchestration layer

At this level, business processes are modeled, controlled and monitored, usually on the basis of BPMN or own representations of the process flows. This layer defines the logic: Which tasks are carried out when, by whom or what?

2. automation layer

This layer ensures the actual implementation. Whether API-based backend integration, RPA in the frontend or mixed models – automation follows the process logic and remains transparently controllable. Ideally, these automation components can be exchanged in a targeted manner, enabling continuous improvement of automation that adapts to the changing requirements and technologies of your company.

3. intelligence layer

This is where AI comes into play. AI models recognize patterns, interpret content, prioritize tasks or suggest improvements. The explainable AI (xAI) approach is important here: AI supports, explains and expands the process, but does not replace it. Even if the AI could make decisions independently based on the growing experience, its degree of freedom is restricted by freely configurable parameters such as the “confident level” or rule corsets so that the results do not pose a risk of incorrect decisions in a professional environment.

4. governance & compliance layer

Every action is documented and is audit-proof. BOAT therefore meets the requirements of GDPR, ISO 9001, ISO 27001 and the EU AI Act – an important criterion for productive use in industries with many requirements.

Rule-Based Automation and Data Processing with AI: Two Perspectives, One Goal Under the Umbrella of BOAT

Basically, the idea of BOAT is to be seen as a single entity from the outside. However, as described above, it has several levels. In many cases, it makes sense to look at these in two subgroups: The actual execution and the analytics, so, metaphorically speaking, into hands and brain. Why is that?

1. innovation cycles

While the areas of automation and orchestration can already boast very advanced solutions, AI is still in its infancy by comparison. As a result, their development leaps are naturally larger and more frequent. Combining both in one product means fewer visible interfaces, but also greater dependencies.

2. range of functions

Although both areas have great potential to complement each other and thus create synergies, they can also easily serve as an extension for other areas without much additional effort. If you do not want to limit these functionalities by “housing” them exclusively in the BOAT strategy, open systems whose functions are also accessible from the outside are useful.

3. realization periods

Automation can achieve success very quickly with modern systems. AI systems, on the other hand, often require their own time until they are resilient and reliable. If you consider a strategy of phased introduction, separation can also offer advantages. “Automation first” and decoupling the implementation of AI in terms of time. There is enough potential in every company to start with a rule-based approach and gradually combine automation with AI. This makes sense from both a commercial and resource perspective.

The automation and orchestration platform, such as the meta:suite, therefore forms the technological backbone of a BOAT architecture in this case. As mentioned, it should be an open, system-independent platform for process modeling, control and automation. It should be open to systems so that it can be easily integrated into an existing company architecture, but also be usable for external systems at a later date. This applies not only to functional aspects, but also to administrative and operational aspects. Ideally, operational and administrative functions of the platform itself can be integrated into already automated processes, e.g. in IT incident or performance management.

The strength of this area lies in the complete control of technical processes – from data acquisition and workflow management to complex decision models. It integrates back-end systems, APIs and front-end applications in equal measure, creating a consistent process logic.

Intelligent data processing based on AI, such as the moresophy ContextSuite, adds the semantic dimension to this view: it understands content, puts data into context and makes unstructured information machine-readable. BOAT therefore offers a combination of process control and an understanding of the context of the content – i.e. why a process is created, what meaning information has and how it is to be classified in the process context. Here too, creating an open, “generalist tool” is highly beneficial. AI training is often time, resource and data-intensive. The “knowledge” acquired and maintained in this way can be of great value in many processes outside the BOAT environment.

The Benefits for Companies

Companies that apply BOAT principles have advantages on various levels:

• End-to-end automation:
  Processes run across system boundaries without media discontinuity.
• Faster processes:
  Automations can be flexibly combined and expanded.
• Comprehensible decisions:
  xAI-supported rules ensure that every decision can be explained.
• Reduced complexity:
  specialist departments can model processes without having to know the technology in detail.
• Compliance by design:
  Governance, data protection and audit trails are an integral part of the framework.
• Control:
  Above all, however, a new level of transparency and controllability is created. Processes are not only automated, but also controlled – an important prerequisite for the digital sovereignty of modern companies.

A Look into the Future

Business Orchestration and Automation Technology marks the transition from pure efficiency enhancement to intelligent business management. While many AI applications improve individual sub-areas, BOAT combines operational execution with semantic understanding – the foundation for a new generation of data-driven companies.

The future belongs to companies that combine both: structured process thinking and semantic intelligence.

BOAT is therefore not a vision, but a basic attitude: the desire to design business processes in such a way that they are intelligent, explainable and infinitely adaptable.