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Making AI Secure with Retrieval-Augmented Generation and the Apryse Server SDK

By John Chow | 2024 Jun 28

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2 min

Summary: The Apryse Server SDK offers a secure and flexible solution for building private RAG datasets, ensuring sensitive information remains protected. This versatile document SDK can be deployed on any self-hosted server, including private clouds, providing complete control over documents and eliminating the need for third-party hosting. With the SDK APIs, users can build a RAG database or corpus while maintaining full security and oversight.

Introduction

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The AI technology world is moving fast, Retrieval-Augmented Generation (RAG) AI stands out for its unique approach to data synthesis. By combining the best of retrieval-based and generative AI models, RAG AI offers a powerful tool for creating accurate and contextually relevant responses. However, when AI is being used on sensitive information, the data security of the AI and its dataset is paramount. This is where the Apryse Server SDK comes into play, offering a secure and flexible solution for dataset construction.

Understanding RAG AI

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RAG AI works by retrieving information from a vast dataset. then uses a generative model to refine that information into coherent and contextually appropriate content. This process allows RAG AI to produce high-quality outputs that are both informative and reliable with minimal hallucinations or factually incorrect answers. However, the security of the underlying dataset is crucial; if the dataset is compromised, so too is the integrity of the AI’s output. If the nature of the documents is private, the data flow of the document must be kept secure.

The Role of Apryse Server SDK

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The Apryse Server SDK is a flexible document SDK that can be deployed on any manner of self-hosted servers (including private cloud) and platforms. Because it is entirely self-hosted or administered, sensitive documents are under complete control and scrutiny to build a RAG database or corpus through the SDK APIs. There is no need to send documents to a third party for hosting and processing.

Flexibility and Security

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One of the key advantages of the Apryse Server SDK is its flexibility. Developers can build with the SDK to their specific needs, choosing which documents to include in the dataset and how to process them. This customization ensures that the resulting RAG data is highly relevant to the AI’s intended application. By allowing for private deployment, it ensures that the document refinement process is insulated from external threats. This is crucial for industries where data sensitivity is a concern, such as healthcare, finance, and legal services.

Refining Documents into RAG Data

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The process of refining documents into RAG data is both an art and a science. The Apryse Server SDK excels at this by providing tools that help with the extraction and processing of information from documents. A data scientist does not require knowledge of document structure or file format and conversion. They can focus on the data within the document and manipulate it into a form ready for RAG AI retrieval. This not only speeds up the dataset construction but also enhances the security of the data, as the refinement process is contained within a controlled environment.

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Explore the benefits of Retrieval-Augmented Generation (RAG) and see how the Apryse Server SDK can streamline your data extraction process for building custom datasets.

Conclusion

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The inherent security of RAG AI is bolstered by using an SDK like Apryse. With its combination of document processing abilities and deployment flexibility, the Apryse Server SDK stands out as the most secure solution for privately deploying and refining documents into RAG data. As AI continues to advance, the importance of secure dataset construction will only grow, making solutions like Apryse all the more essential.

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John Chow

Product Manager

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