Framework Compatibility
Work with your favorite Python and RAG frameworks like LangChain and LLamaIndex.
AI app and workflow templates
In-Database RAG - Retrieval Augmented Generation
Easily build generative AI RAG applications, such as AI chatbots, directly on your database.
Features in RAG Database
End-to-End Workflow
Have the end-to-end RAG workflow contained in your database.
Instant Processing
Have new incoming data instantly processed and made available to your applications.
Scalable Deployment
Implement and scale various RAG applications side-by-side with one deployment, reusing workflow steps across your applications if possible.
API Switching
Switch between AI APIs and the latest self-hosted embedding and language models.
Fine-tune Models
Fine-tune LLMs with your data for optimal performance and accuracy.
Use Cases
Framework Compatibility
Easily integrate with popular Python frameworks like LangChain and LLamaIndex to streamline the development of your AI applications.
End-to-End Workflow
Maintain the complete RAG workflow within your database to simplify data management and processing tasks.
Real-Time Data Processing
Ensure new incoming data is instantly processed and made available for immediate use in applications, enhancing responsiveness.
Scalable Deployment
Deploy and scale multiple RAG applications concurrently, optimizing resource usage and performance across all applications.
API Switching
Easily switch between various AI APIs and the latest self-hosted models to leverage the best technologies for your needs.
Fine-Tuning
Customize large language models (LLMs) with your specific data to enhance their accuracy and performance for your applications.
Customer Support
Implement AI chatbots to provide instant, accurate responses to customer queries by leveraging real-time data processing.
Automated Analysis
Use RAG to analyze and generate insights from large volumes of documents, automating tasks like compliance checks and report generation.
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