How Amplitude implemented natural language-powered analytics using Amazon OpenSearch Service as a vector database | Amazon Web Services

How Amplitude implemented natural language-powered analytics using Amazon OpenSearch Service as a vector database | Amazon Web Services

This is a guest post by Jeffrey Wang, Co-Founder and Chief Architect at Amplitude in partnership with AWS.

Amplitude is a product and customer journey analytics platform. Our customers wanted to ask deep questions about their product usage. Ask Amplitude is an AI assistant that uses large language models (LLMs). It combines schema search and content search to provide a customized, accurate, low latency, natural language-based visualization experience to end customers. Ask Amplitude has knowledge of a user’s product, taxonomy, and language to frame an analysis. It uses a series of LLM prompts to convert the user’s question into a JSON definition that can be passed to a custom query engine. The query engine then renders a chart with the answer, as illustrated in the following figure.

Amplitude’s search architecture evolved to scale, simplify, and cost-optimize for our customers, by implementing semantic search and Retrieval Augmented Generation…

https://aws.amazon.com/blogs/big-data/how-amplitude-implemented-natural-language-powered-analytics-using-amazon-opensearch-service-as-a-vector-database/