Vectorize: a vector database for shipping AI-powered applications to production, fast

Introducing Vectorize, a vector database for Cloudflare Workers that enables semantic search using precomputed embeddings from any text or embedding API, including Workers AI and OpenAI's Embedding API. With pricing based on the total number of vector dimensions queried and stored, it aims to provide predictable costs without limiting features like per-index analytics and sub-index filtering capabilities. Vectorize is currently in open beta for all Cloudflare Workers developers with a paid plan, allowing them to start building semantic search applications immediately. The tutorial on how to combine OpenAI's Embedding API and Vectorize showcases an example of using the database for document search, while other use cases include enhancing large language models (LLMs) by giving them more context or providing multilingual capabilities through the BYO embeddings feature that supports popular embedding APIs like Cohere. Developers can join a dedicated Discord channel to discuss their ideas and get support from Cloudflare's product and engineering teams for building on Workers AI. The announcement of Vectorize as an addition to the existing suite of tools available in the serverless computing environment provided by the article mentions about other upcoming changes like introducing sub-index filtering capabilities, increased metadata limits. CloudflareVectorize (coming soon) - (total queried dimensions inclu) :``` SUMMARY: Cloudflare Workers AI Vector Database Semantic Search Pricing Predictability BYO Embeddings Indexes Large Language Models OpenAI Cohere Metadata Limits Latency Beta Cloudflare Workers AI Semantic Search Precomputed Embeddings Workers Paid Plans Discord Channels Product Engineering Support