“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 GenAI apps. RAGStack includes the best open-source for implementing RAG, giving developers a comprehensive GenAI Stack leveraging LangChain, LLamaIndex, and more.
Production RAG apps with LangChain, LLMs and Vector Search
Join Harrison Chase, founder and CEO of LangChain and Tisson Mathew, Founder and CEO of Skypoint as they share hard-earned insights deploying production RAG apps harnessing customer data with the power of LangChain, Large Language Models (LLMs), and Vector Search.
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 GenAI Performance
RAGStack is designed to enhance GenAI 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 ReAct) and the LangChain and LLamaIndex ecosystem to continually improve GenAI accuracy. RAGStack adds new open source software to provide enterprise users a predictable upgrade path as new techniques emerge.
Enterprise Governance and Compliance
RAGStack is backed with enterprise support and SLAs, supporting HIPAA, TRUSTe, SOC2 compliance when running with 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.
