This n8n workflow is designed to analyze text from an NDA (Non-Disclosure Agreement) for potential risks, using AI models and vector similarity search. It enables organizations to automate the review process of NDA documents, assessing risky content efficiently.
The workflow begins with a Webhook trigger, which accepts incoming NDA text submissions. This text is then split into manageable chunks using a character-based text splitter to prepare it for analysis.
Each chunk is processed through a Hugging Face embeddings node to generate vector representations, which are stored in a Redis vector database for efficient similarity searches. When a new NDA text is analyzed, it is compared against the existing embeddings in the database to identify potential risks based on semantic similarity.
The workflow incorporates an AI language model (OpenAI) with a custom agent that defines and executes risk assessments based on the text prompts. The AI agent utilizes a memory buffer to maintain context during its analysis.
Subsequently, the results of the risk analysis, along with the original NDA content, are logged into a Google Sheets document for record-keeping and review.
Practical use cases include automating NDA risk assessments, ensuring compliance, and saving time for legal teams by quickly flagging potentially risky clauses in confidential documents.
This workflow is suitable for legal, compliance, and data security teams looking to streamline document review through AI-powered automation.
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