Written By: Kumar Shanu, Machine Learning Specialist, Rapyder Cloud Solutions
Generative AI is a powerful technology that can create new content from existing data. It can be used for various applications such as text generation, image synthesis, speech synthesis, and more. One of the most popular examples of generative AI is ChatGPT, a conversational agent that can chat with humans on various topics using natural language.
However, ChatGPT is not designed to handle enterprise data, which may have specific domain knowledge, terminology, and privacy requirements. That’s why we have developed a solution that allows enterprise customers to use generative AI for their own data. Our solution enables you to create a chatGPT-like experience over your own data using state-of-the-art generative models such as OpenAI’s ChatGPT.
Our solution provides the enterprise customers with the capabilities to use generative AI for their enterprise data. It can help you improve your customer service, employee engagement, business intelligence, and more.
How it works:
Our solution uses two powerful technologies: OpenAI GPT3.5-turbo model and Azure Cognitive Search. The GPT3.5-turbo model is a large-scale language model that can generate natural and coherent text on any topic. Azure Cognitive Search is a cloud service that allows you to easily index and query your data. By combining these two technologies, we use a technique called Retrieval Augmented Generation (RAG), which enables the generative AI application to respond from the user data only. This technique allows Generative AI model to response to the user’s query based on the knowledge received from the search index created by Azure Cognitive Search.
What is Azure Cognitive Search:
Azure cognitive search is a cloud-based service provided by Azure which uses advanced AI capabilities to search and enable content discovery across your data. It uses advance built-in ML technologies to understand user intent then provided with the most relevant search result. Azure Cognitive Search service creates two major components i.e., Indexer and Index.
Indexer:
An Indexer is a crawler that extracts the searchable content form the data sources and creates a search index. Indexer automatically scans through the data sources and extract content from that. It also creates field to field mapping between data source and search index.
Index:
An Index is document which contains all your searchable content along with the fields, enhanced content, and insights. Index is available to the search engine to make queries and providing the search results.
Features:
- Talk with your data as it is a human.
- Enable semantic search on your data.
- More personalized results only from your data.
- Chat and QnA
- Various options for users to evaluate trustworthiness with citation and tracking of content.
- Settings to tweak behaviour of Gen AI model.
- Monitoring and reporting
- Fully managed Service
- Good User Experience
Business Use cases:
This solution can be used in many domains and industries which deals with a huge amount of data and a lot of documents. Some examples are Banking, Fintech, Edtech, Healthcare, legal firms, and Government.
Conclusion:
It is a very powerful solution which Rapyder provides as a packaged solution. Customers do not need to be worried about deploying and managing anything, Rapyder is here for you.
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