This n8n workflow automates the detection and logging of GDPR violations based on incoming webhook data. It facilitates real-time analysis and documentation to ensure compliance with data protection regulations.
The workflow begins with a webhook trigger that receives data related to potential GDPR violations. The data is then processed by a text splitter node, which divides the content into manageable chunks for analysis. These chunks are converted into embeddings using OpenAI’s API, enabling semantic comparison and retrieval.
The embeddings are stored in a Supabase vector database to facilitate efficient searches. When a new violation report arrives, the system queries the database to find similar past violations or related entries, enhancing anomaly detection.
An AI language model (via Hugging Face) is employed to analyze the context and severity of the violation, generating a detailed report. This report is then logged into a Google Sheet for record-keeping. The entire process leverages nodes for vector storage, embedding, and AI analysis, integrating seamlessly to provide automated GDPR violation alerts and documentation.
This workflow is ideal for organizations wanting to automate the monitoring and logging of GDPR-related issues, ensuring quick response and maintaining compliance with minimal manual intervention.
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