How to build real-time AI applications without managing vector databases or infrastructure

How to build real-time AI applications without managing vector databases or infrastructure

This task can be performed using Orchata

Knowledge infrastructure for AI agents. Fast by default.

Best product for this task

Orchat

Orchata

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Orchata is the fastest way to give your AI agents access to knowledge. Upload PDFs, docs, or markdown, and we handle chunking, embedding, and indexing automatically. Query from anywhere via our TypeScript SDK, REST API, or native MCP server. Built for real-time applications with sub-150ms P50 retrieval. No vector database to manage, no infrastructure to maintain.

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What to expect from an ideal product

  1. Upload your documents and Orchata automatically chunks, embeds, and indexes them so you don't need to set up vector databases or write complex preprocessing code
  2. Get sub-150ms response times for document retrieval without worrying about database optimization, scaling, or performance tuning
  3. Connect to your app through TypeScript SDK, REST API, or MCP server instead of managing multiple database connections and infrastructure components
  4. Focus on building your AI features while Orchata handles all the backend knowledge storage and retrieval behind the scenes
  5. Deploy real-time AI apps faster since there's no database provisioning, embedding model setup, or server maintenance required

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