Infinidat launches RAG for GenAI​

​

The accuracy of generative AI (GenAI) gets a boost as Infinidat launches its Retrieval-Augmented Generation (RAG) workflow solution to dramatically improve the accuracy and relevancy of AI models with up-to-date, private data from multiple company data sources, including unstructured data and structured data, such as databases, from existing Infinidat platforms.

With RAG architecture enterprises can utilize Infinidat’s existing InfiniBox® and InfiniBox™ SSA enterprise storage systems as the basis to optimize the output of AI models, without the need to purchase any specialized equipment.   Users also have the flexibility to use RAG in a hybrid multi-cloud environment with Infinidat’s InfuzeOS™ Cloud Edition, making the storage infrastructure a strategic asset for unlocking the business value of GenAI applications for enterprises.  

“Infinidat will play a critical role in RAG deployments, leveraging data on InfiniBox enterprise storage solutions, which are perfectly suited for retrieval-based AI workloads,” says Eric Herzog, Chief Marketing Officer, Infinidat.  “Vector databases that are central to obtaining the information to increase the accuracy of GenAI models run extremely well in Infinidat’s storage environment.  Our customers can deploy RAG on their existing storage infrastructure, taking advantage of the InfiniBox system’s high performance, industry-leading low latency, and unique Neural Cache technology, enabling delivery of rapid and highly accurate responses for GenAI workloads.”

Inaccurate or misleading results from a GenAI model, referred to as “AI hallucinations,” are a common problem that have held back the adoption and broad deployment of AI within enterprises.  “An AI hallucination may present inaccurate information as “fact,” cite non-existent data, or provide false attribution – all of which tarnish AI and expose a gap that calls for the continual refinement of data queries. A focus on AI models, without a RAG strategy, tends to rely on a large amount of publicly available data, while underutilizing an enterprise’s own proprietary data assets,” explains Herzog.

“To address this major challenge in GenAI, Infinidat is making its architecture available for enterprises to continuously refine a RAG pipeline with new data, thereby reducing the risk of AI hallucinations.  By enhancing the accuracy of AI model-driven insights, Infinidat is helping to advance the fulfillment of the promise of GenAI for enterprises.”

“Infinidat is positioning itself the right way as an enabler of RAG inferencing in the GenAI space,” comments Marc Staimer, President, Dragon Slayer Consulting.  “Retrieval-augmented generation is a high value proposition area for an enterprise storage solution provider that delivers high levels of performance, 100% guaranteed availability, scalability, and cyber resilience that readily apply to LLM RAG inferencing.  With RAG inferencing being part of almost every enterprise AI project, the opportunity for Infinidat to expand its impact in the enterprise market with its highly targeted RAG reference architecture is significant.”