This blog post is a collaboration between the author and Tuana Çelik from deepset, focusing on the importance of enterprise search in document digitization and knowledge management. The post introduces the concept of large language models (LLMs) and how they can be used to enhance enterprise search by providing conversational experiences to users. However, it is crucial to ensure that LLMs are limited to company data to avoid model hallucinations. The post showcases how to build an end-to-end generative AI application for enterprise search using Retrieval Augmented Generation (RAG) with Haystack pipelines and the Falcon-40b-instruct model from Amazon SageMaker JumpStart and Amazon OpenSearch Service. The post provides an overview of the solution, including the steps involved in the retrieval augmentation workflow. It also introduces SageMaker JumpStart, Haystack, and Amazon OpenSearch as the key tools used in the application. The post concludes by mentioning the availability of the source code for the showcased sample in a GitHub repository and provides instructions on prerequisites and how to index documents to OpenSearch.
Creating Enterprise Search AI Applications with Haystack Pipelines and Amazon SageMaker JumpStart: Harness the Power of LLMs
