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KnowledgeRAG: answers from your own documents

Connect your documents, websites, and knowledge bases to LLMs for more accurate, context-aware AI responses.

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Everything Your AI Needs to Access Your Knowledge

KnowledgeRAG connects your documents and data sources to large language models, with citations back to the source.

Universal Data Connectors

Connect to virtually any data source including documents, websites, knowledge bases, and enterprise systems.

Automatic Data Processing

KnowledgeRAG extracts text from documents, processes images, and transcribes audio and video content.

Semantic Search

Powerful vector-based semantic search finds information based on meaning, not just keywords.

LLM Integration

Seamlessly integrate with popular LLMs like GPT-4, Claude, and open-source models.

How It Works

Get started in minutes with our simple implementation process.

1

Connect Your Data

Use our connectors to import your documents, websites, and enterprise data.

2

Configure Your Knowledge Base

Set up data processing rules, create custom taxonomies, and define access controls.

3

Integrate with LLMs

Connect to your preferred LLM through our API or use our managed LLM integrations.

4

Deploy Your AI Application

Build chatbots, search applications, or knowledge assistants powered by your data.

Frequently Asked Questions

Find answers to common questions about our RAG platform.

What is Retrieval-Augmented Generation (RAG)?

RAG is an AI architecture that enhances Large Language Models by retrieving relevant information from external knowledge sources before generating responses. This allows AI to access up-to-date information that wasn't in its training data and provide more accurate, context-aware answers.

How does KnowledgeRAG differ from just using an LLM API?

Standard LLM APIs have limited context windows and no access to your specific business data. KnowledgeRAG connects your enterprise knowledge to LLMs, allowing them to provide responses based on your actual data. This solves LLMs' hallucination problems and enables them to answer questions about your specific business information.

What types of data can I connect to KnowledgeRAG?

KnowledgeRAG supports virtually any data type, including documents (PDF, Word, PowerPoint, Excel), images, audio/video files, websites, databases, knowledge bases, and SaaS applications. It automatically processes and indexes this content for AI retrieval.

We build with

Open technology first — and the platforms you already run

Open source / open technology

  • Llama
  • Mistral
  • Qwen
  • DeepSeek
  • vLLM
  • Ollama
  • LangGraph
  • LlamaIndex
  • pgvector
  • Qdrant
  • Spark
  • Kubernetes
  • FastAPI
  • PostgreSQL
  • Keycloak
  • OpenTelemetry

Enterprise providers

  • Microsoft Azure
  • AWS
  • Google Cloud
  • OpenAI
  • Anthropic
  • Google Gemini
  • Mistral AI
  • Databricks
  • Snowflake
  • Microsoft Fabric
  • Microsoft 365
  • SAP
  • Salesforce

Technologies we work with, chosen per project — not a list of partnerships or certifications.

See the full stack →

Ready to supercharge your AI with enterprise knowledge?

Tell us about your data and we will show you what KnowledgeRAG can do with it.

Request a demo