Update README.md

README.md

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 # The GDPR Input Detection and Anonymization model
 
-The **The GDPR Input Detection and Anonymization model**  is designed to protect sensitive information locally before it is processed by larger AI models in external clouds. 
-
-External cloud suppliers store every input for at least 30 days!
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-Inference costs of small or big model differ by factor 100!
-
-You can't give LLM access to employees without caring about GDPR and company compliance.
+The **The GDPR Input Detection and Anonymization model**  is designed to protect sensitive information locally before it is processed by larger AI models in external clouds.
 
 
 ## Intended Use
 
-The model is made to bridge the user inputs to external LLM input like a firewall or proxy
+The model is made to bridge the user inputs to external LLM input like a firewall or proxy.
 
 The model analysis the user prompts and computes two scores. 
 
-The first score helps to identify if it needs a small or more cabable model to process the user input. The second score rates the sensitivity of the prompt. When it detects sensitive information, the further cloud processing of the prompt can be blocked or at least be replaced by an anonymized version.
+The first score helps to identify if it needs a small or more cabable model to process the user input. 
+
+The second score rates the sensitivity of the prompt. When it detects sensitive information, the further cloud processing of the prompt can be blocked or at least be replaced by an anonymized version.
 
 
 ## Complexity Scoring