SciPhi

Effortlessly build, deploy, and scale Retrieval-Augmented Generation (RAG) systems

Focus on AI innovation while SciPhi handles the infrastructure

Configure your RAG pipeline to your exact needs using the config.json

Customize your R2R RAG pipeline directly by modifying the underlying code

Deploy production-ready RAG pipelines with just one click

Evaluate and monitor each pipeline performance with built-in capabilities

Flexible Document Ingestion with support for various file formats

Robust Document Management with the ability to update or delete vectors

Feature Rich with the ability to select from many LLM and vector database providers

Configurable Provider to seamlessly connect with third-party data retrieval sources

Adaptable to customize your RAG pipeline by integrating additional plug-ins or proprietary data

Dynamic Scalability to autoscale up and down available compute with user demand

SOTA Techniques with one-click deployment of latest techniques such as HyDE, RAG-Fusion, and Agentic RAG

Configurable & Customizeable to specify providers, adjust settings, and optimize performance

Transform conversational AI systems into intelligent assistants capable of handling complex inquiries by augmenting their responses with retrieved information