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AI Data Processing
Updated over a week ago

In order to address concerns regarding the use of the AI model provided by OpenAI,
we would like to highlight the most important points in connection with the data we
transmit and its processing.

Legal Framework:
From a legal standpoint, it is crucial to distinguish between two categories of data:
Personal Data and non-personal Data. Personal Data encompasses information that
allows the identification of an individual, such as data of birth, name, sex, IP address,
and company name

We are legally obliged to make the processing of personal data transparent. We
would like to point out that all relevant information on the handling of personal data
is contained in our current data processing agreement (GTC & DPA). Our
commitment to data protection is reflected in our strict adherence to the guidelines
set out in these documents.

Data Handling Protocol:
We want to assure you that we do not transmit personal data to OpenAI unless
explicitly entered into the textbox by the user. This ensures that sensitive information
is not inadvertently shared or processed without proper authorization.

The following applies to the AI assistant FlowShare Assist and AI-Text Generation:
The data is converted into vectors (number collons) with the help of Azure OpenAI
and stored in a vector database hosted in the EU. Everything runs via the Azure
OpenAI service, which is hosted in the EU and all data is processed in compliance
with the GDPR.

Secure Processing of Your Company Information with Azure OpenAI Service:

Your prompts (inputs) and completions (outputs), your embeddings, and your
training data:

are NOT available to other customers.
are NOT available to OpenAI.
are NOT used to improve OpenAI models.
are NOT used to improve any Microsoft or 3rd party products or services.
are NOT used for automatically improving Azure OpenAI models for your use in your
resource (The models are stateless, unless you explicitly fine-tune models with your
training data).

Your fine-tuned Azure OpenAI models are available exclusively for your use.

We are currently working on the implementation of PII and NER.

Personally Identifiable Information (PII)
PII recognition is a function offered by Azure AI Language.
The PII recognition function can identify, categorize and redact sensitive information
in structureless texts. Examples include phone numbers, email addresses and forms
of identification.

Named Entity Recognition (NER)
NER is a function offered by Azure AI Language.
The NER function can identify and categorize entities in structureless texts.
Examples include persons, places, organizations and quantities.

Regarding the AI-Auto Translation via DeepL:
DeepL is a German company and processes data in Germany. It is therefore also
subject to the EU Data Protection Regulation.

More information on their general terms and conditions and their data security can
be found here:

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