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Docubix

AI-powered custom RAG database and chat assistant builder.

Reviewed by Editorial Board • Fact-Checked: 2026 Standards • Testing Status: Verified & Tested

Quick Keypoints

  • Trained custom AI chat assistants on uploaded PDFs, DOCX, and text files.
  • Generates answers with automatic citations linking back to original pages.
  • Enables multiple knowledge bases for documentation and onboarding guides.
  • Provides REST APIs and webhooks for developers to stream responses.

What is Docubix?

AI-powered custom RAG database and chat assistant builder.

Docubix is an AI-powered knowledge base and Retrieval-Augmented Generation (RAG) platform. It allows users to upload documents and create custom AI assistants that answer questions based solely on the provided files, with citations linking back to the source page or section.

Who Needs Docubix?

SaaS founders, customer success managers, researchers, and technical writers.

Primary Use Cases

  • Creating a searchable internal wiki or employee onboarding resource.
  • Building client-facing AI assistants trained on product manuals.
  • Summarizing and extracting facts from large research paper libraries.

Important Features

  • AI Assistant Widget: An embeddable chat assistant widget for websites.
  • Knowledge Bases: Create and segment multiple database sources.
  • Developer API: Stream responses and sync conversation histories natively.

Current Updates About Docubix

  • Docubix offers a developer-first RAG pipeline as a service, supporting DOCX/PDF upload, scoped API keys, and streaming chat endpoints with citations.
  • Current Version: v1.0

Alternatives to Docubix

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Pricing Plans

Plan Price
FreeProvides 1 knowledge base, up to 20 documents, 100 queries/month, 0.25 GB storage, and cited answers. $0/mo
ProUnlocks 10 knowledge bases, up to 1,000 documents, 3,000 queries/month, 10 GB storage, and API access. $79/mo

Editorial Verification

Independent Testing

This review was audited under our 5-Pillar Testing Framework: Output Quality, UI/UX Ease, Pricing Transparency, Feature Depth, and Support.

Read Our Review Methodology →

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