“DataStax technology is deeply integrated into our generative AI infrastructure. We’ve built our solution with Astra DB and customized open source software like LangChain – this is what we have in production today. With RAGStack, we’ll be able to reduce the pain of maintaining customized open source software , helping to deliver a more simplified and streamlined healthcare AI solution for our customers”
RAGStack
Production-Ready RAG
RAGStack is an out of the box solution simplifying Retrieval Augmented Generation (RAG) in AI apps. RAGStack includes the best open-source for implementing RAG, giving developers a comprehensive Gen AI Stack leveraging LangChain, CassIO and more.
Benefits
Ready-Made RAG Solution
Rapid deployment for RAG apps
Improve developer productivity and system performance with orchestration and prompt templates, unstructured data store abstraction, natural language to structured query abstraction, agent memory abstraction, and LLM caching abstraction.

Improved Gen AI Performance
RAGStack is designed to enhance Gen AI app performance with tested techniques for prompt engineering, prompt retrieval and different data types - reducing hallucinations and improving contextual relevance.

Continuous Evolution with Advancements
RAGStack seamlessly updates to RAG techniques (such as FLARE) and the LangChain ecosystem to continually improve Gen AI accuracy. As new techniques emerge and new software is developed, RAGStack will add new open source software to provide enterprise users a predictable upgrade path.

Enterprise Governance and Compliance
RAGStack is backed with enterprise support and SLAs, easily supporting HIPAA, TRUSTe, SOC2 compliance when running in Astra DB.

Scalability and Cost-Effectiveness
Scale easily with the increase in data and usage. RAGStack is designed to improve response times, scale easily with the increase in data and user base, and lower the cost of LLMs by caching a large percentage of calls.
