AI-powered workplace search: how it works, benefits, and more

What this post added

This post details the technical implementation of an AI-powered workplace search using Meilisearch. It outlines the steps involved: installing and launching Meilisearch, connecting it with the OpenAI API, defining document structures (including role-based access control), configuring the Meilisearch index with specific fields and vector embeddings, generating embeddings for document titles and content using OpenAI's text-embedding-3-small model, and indexing these documents with their embeddings into Meilisearch. It also explains how user queries are converted into vectors for semantic search and how Meilisearch's capabilities can be leveraged to build such search engines.