[PLUGIN] Build AI Knowledge Bases in Under 5 Minutes

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We just released VectorDoc Search, a new plugin built on Bubble that lets you add semantic document search to your app in under five minutes.

This plugin focuses on retrieval. It helps you find the most relevant content from your own documents based on meaning, not keywords.

If you want AI-generated answers, you can optionally connect the search results to your own OpenAI key. This keeps the setup flexible and under your control.

What it does

  • Upload documents (PDF, TXT, or any text-based file)
  • Search documents using natural language
  • Retrieve the most relevant text chunks
  • Get similarity scores for each result
  • Use the results as context for RAG-style workflows if needed

Security & namespaces

  • Documents are stored and queried using namespaces
  • Each namespace is isolated
  • Ideal for multi-tenant apps (per user, organization, workspace, or project)
  • Searches only return results from the specified namespace
  • API access is handled securely via RapidAPI
  • No personal data is collected or tracked by the plugin

Common use cases

:backhand_index_pointing_right: Semantic document search
:backhand_index_pointing_right: Internal documentation lookup
:backhand_index_pointing_right: Customer support tools
:backhand_index_pointing_right: RAG-style apps (semantic retrieval + your own LLM)
:backhand_index_pointing_right: Content-aware automations

Quick start (under 5 minutes)

  1. Subscribe to VectorDoc on RapidAPI
  2. Install the plugin in your Bubble app
  3. Upload documents to a namespace
  4. Query using natural language
  5. Receive ranked results with similarity scores

Documentation

API access

How VectorDoc Search differs from Pinecone

Pinecone is a powerful vector database, but it’s designed primarily for developers and production-scale infrastructure. For many Bubble builders, that comes with extra complexity and cost.

Key differences:

1. Pricing & accessibility
Pinecone’s paid plans typically start around $50/month, even before you’ve fully validated your use case.

VectorDoc Search is accessible via RapidAPI and is designed to be low-friction and cost-effective, especially for MVPs and early-stage apps.

Keywords

Semantic Search • RAG • Vector Database • Embeddings • Knowledge Base • Pinecone

Feedback is welcome.

Link: Vectordoc Search RAG Plugin | Bubble

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