Semantic search can be combined with generative AI to create even more powerful and intelligent search systems. Generative AI, such as language models like GPT-3, is capable of generating human-like text based on the input it receives. By integrating generative AI with semantic search, we can enhance the search capabilities and provide more natural and contextually relevant responses to user queries.
Improved Query Understanding
Semantic search can understand the context and intent of the user’s query better, and this enriched understanding can be used as input to the generative AI model. The generative AI can then generate more comprehensive and contextually relevant responses, which go beyond keyword-based matching.
The Essentia development team has created a prototype of an AI based search assistant that combines semantic search and generative AI to make a more natural and intuitive query system for documents. By leveraging the strong OCR and content search/filtering of Essentia AI with the context driven semantic database and GPT 3.5, we tried to explore the possible use cases of such a system for practical usage in a business or personal capacity.
Examples
The following examples show how we applied a variety of different documents through the system and the actual results we saw.
Use case 1: Journalism or Academic Research
Use case 2: Analyzing Books or Manuals
Use case 3: Analyze Business Agreements
Use case 4: User Friendly Help Pages
Final Thoughts
Overall, combining semantic search with generative AI can significantly enhance search experiences by providing more contextually relevant and natural responses, leading to improved user satisfaction and better information retrieval capabilities. If you are interested in finding out more, you can contact us at info@auriq.com and request a demo.
