Your Core. Your workflow. The right operation.

The architecture behind the shared Core.

The technical foundation connects a browser interface, server application, data storage and configurable AI integrations. Specialist modules use this foundation for their respective tasks.

1. Browser interface

   Blazor WebAssembly provides the working views. Staff work in their specialist areas; a change of task does not automatically require a new application.

2. Server and business logic

   ASP.NET Core provides interfaces and professional workflows. Authentication, organisation context and roles are part of the technical architecture. Their actual enforcement must be checked for the agreed use.

3. Data and documents

   A SQL database represents organisations and professional records, among other things. Document, search and export paths complement the specialist functions; their scope depends on the module.

4. AI integration

   A provider interface connects the application to the configured model. The source includes Azure OpenAI, OpenAI and local models through Ollama, among others. Configuration and actual availability are checked for each use.

What role does Microsoft Azure play?

Azure can provide the operating environment for a web application and its interfaces, for example through Azure App Service. Where professional data is stored and which model provider processes AI requests are separate decisions.

The software's Azure OpenAI integration exists in the source. This does not imply a general commitment to a specific Azure region, model, deployment type or continuously available quota.

Microsoft distinguishes regional, Data Zone and global processing paths for model deployments. The specific deployment and data flows are therefore checked before use. Storage functions and operational monitoring must also be considered.

Microsoft: Azure App Service · Microsoft: data processing for Azure models

How information becomes a working step.

1. Request and context

   Information belongs to a person, property, project or case. The necessary assignments and documents depend on the specialist module.

2. Define support

   For the specific workflow, decide which sources and details are used and whether AI is needed at all. Knowledge search, drafting and rule-based scheduling checks are different methods.

3. Check the result

   When a model is used, it provides an answer or suggestion. The professionally responsible people check content, completeness and suitability for the next step.

4. Continue in the specialist workflow

   The checked result is used, supplemented or exported in the intended workspace. Storage, history and export follow the available functions of the respective module.

Privacy belongs in the configured workflow.

Appropriate use requires software, operating environment and working practices to fit together. Before introduction, we clarify the required protection with those responsible for each area.

1. Access and responsibilities

   Who needs which data? Organisation context, roles and effective permissions are checked for the intended use.

2. Required information

   Which inputs and documents does the task need? Define what is stored and what may be sent to an AI provider.

3. Operating location and contracts

   Agree hosting, model deployment, involved providers and required data-processing agreements for the specific data path.

4. Retention and operation

   Agree responsibilities for deletion, backup, recovery and technical or organisational safeguards. Involve the responsible privacy professionals for sensitive specialist information.

This description explains preparation and the building blocks to check. It is not a general certification or a promise that every possible use is automatically GDPR-compliant.