Generative AI
Background
This customer, a GenAI service provider, manages the daunting task of processing hundreds of billions of data records and millions of queries every day. Facing challenges such as data volume management, maintaining query speed, and ensuring accurate analytics, they require an AI RAG system capable of performing real-time analytics on massive datasets.
Customer Pain Points
High cost of storage and retrieval
Managing hundreds of billions of vectors costs tens of millions per month, creating financial strain.
Performance bottlenecks
The legacy system struggles to handle millions of daily queries with sub-100ms response times, affecting real-time performance.
Low search accuracy
Poor search accuracy and lack of multi-path recall mechanisms lead to unreliable results, impacting business effectiveness.
Complex infrastructure dependencies
Managing multiple retrieval components adds complexity, with each new tool requiring security approval and creating operational inefficiencies.
AI-powered data analysis
RAG
(Retrieval-Augmented Generation)