Unlocking the Power of Oracle 23ai: Quistor's AI-Driven Search Tool

Author: Begoña Villamor Manager Business Analytics & Big Data @Quistor

Quistor has developed an innovative tool that harnesses the potential of Oracle 23ai's AI capabilities, revolutionising the way you search and interact with your data. With this tool, you can now perform semantic searches, leveraging natural language to find the information you need within your content.

Semantic Search with Oracle 23ai

  • Natural Language Search: Oracle 23ai's vector search feature enables you to search for content using natural language, going beyond literal keyword searches. This means you can ask questions and find relevant information more intuitively.
  • Combining Structured and Unstructured Data: The tool allows you to combine searches on unstructured data with regular structured filters, providing a comprehensive search experience.
  • Security Assurance: Rest assured that your data remains secure as it never leaves your database during the search process.

How It Works

Initial Setup

  • Store your content or documents in the database.
  • Chunk and vectorise these documents using an AI model.

Usage

  • Vectorise your search query.
  • Calculate the difference between the vectorised query and the vectorised documents, and present the nearest document chunks as results.

Use Case: Intelligent Content Search

Imagine you want to perform an intelligent search on your marketing documents and presentations. With Quistor's tool, you can ask questions like "Quistor functional JDE support service benefits" and receive relevant document fragments as answers.

Generating Natural Language Answers

To enhance the search experience, you can integrate a Gen AI service with the vector search results. This integration allows the tool to generate natural language answers, providing a more human-like response.

Live Demo

Experience the power of Quistor's tool with a live demo. See how it processes documents, vectorises text chunks, and generates summaries using generative AI. The demo also showcases the search process, from vectorising questions to finding the best-fitting text chunks, and finally, generating natural language answers.

Disclaimer

This blog post was generated by OCI Gen AI. While every effort has been made to ensure the accuracy and reliability of the information presented, the content may contain errors or omissions. Please use the information provided as a general guide and consult with experts for specific advice.

Content Source

  • Introduction, disclaimer, and live demo sections: AI-generated content based on the provided document.
  • Vector search and use case sections: Direct quotes and examples from the provided document.
  • Additional information and explanations: AI-generated content to enrich the topic.

Additional Resources

  • For more information on Oracle 23ai and its AI capabilities, visit the official Oracle website.
  • To explore Quistor's tools and services further, visit their website or contact their team.

Note

This QPulse article was created using our Quistor AI tool to demonstrate how Generative AI can help reuse existing content. The tool is based on Oracle 23ai and OCI Generative AI.

We ask Gen AI to write new content based on one of the presentations stored in our marketing database.

This is the prompt we used, the document selected as the knowledge base and the output generated by AI:

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