IBM Storage Scale new features content-aware AI enhancements, ensuring accurate, real-time data processing for enterprise AI applications.
What is content-aware storage?
The purpose of content-aware storage (CAS) is to increase the value of clients’ AI applications through accelerated insights, lower costs, better performance, increased security, and more efficient operations.
Based on research conducted at IBM Research and NVIDIA, these new capabilities make use of novel techniques for representing words and their meanings as vectors series of numbers. This is the secret that enables generative AI programs to extract data that has pertinent meaning in addition to the appropriate keywords. In order to help increase the accuracy of AI tools and enable AI models to remain current with new knowledge without retraining, it expands on retrieval augmented generation (RAG).
New capabilities in Storage Scale
The RAG process is further strengthened by Storage Scale’s new content-aware storage features. IBM expanded on the most recent NVIDIA Blueprint, AI-Q, which makes use of NeMo Retriever, a tool for extracting data from text, graphs, charts, and even pictures. To put organisations in a position to get more business value out of their current data holdings, it accelerated and automated RAG processing.
To ensure that data is up to date for AI applications effectively using NVIDIA accelerated computing, Storage Scale, for example, can monitor folders on other storage systems or in the cloud to detect changes as they happen, automatically run pre-built pipelines, and update only the changes to the vector database. In order to integrate data into your AI factory from IBM and third-party storage environments, Storage Scale additionally offers cutting-edge global data abstraction services designed to offer connection from numerous data sources and locations.
Use-cases for content-aware storage
There are numerous applications for content-aware storage for businesses looking to maximise the business value of their data stores:
Improving AI assistant accuracy
In order to increase accuracy and combat hallucinations, CAS makes sure AI helpers have access to the most recent contextual information.
Up-to-date data insights
In order to allow AI technologies to get insights as events transpire, CAS monitors folders for changes and updates the RAG database as data changes.
Streamlined AI data pipelines
CAS decreases data movement and latency to boost efficiency by integrating computation, data pipelines, and vector database capabilities into the storage system.
Enhanced search
Beyond keyword-matching, CAS makes it easier to find pertinent information by utilising natural language processing to derive semantic meaning from unstructured data.
Additionally supported by Storage Scale is the new NVIDIA AI Data Platform, which lets IT professionals create distributed systems that unleash the value of business data to drive data-driven decisions and ushers enterprise storage into the age of agentic AI. The platform is an adaptable reference design for combining enterprise storage with NVIDIA accelerated processing, networking, and AI software, turning data into useful intelligence.
IBM Storage Scale
Software-defined storage for creating a worldwide platform for analytics, AI, and HPC data.
A worldwide data platform for demanding workloads like advanced analytics, high-performance computing (HPC), and artificial intelligence (AI) is made possible by IBM Storage Scale, a software-defined file and object storage system. It handles unstructured data across dispersed storage environments with ease, including documents, audio, photos, and videos.
Even in non-IBM storage environments, it offers unified access and global data abstraction across x86, IBM Power, IBM Z, ARM-based POSIX clients, virtual machines, and Kubernetes. It is built on a massively parallel file system. Businesses can process and analyse large amounts of data quickly, reliably, and securely with its high performance, scalability, and operational efficiency, maximising the value of their business-critical data.
Additionally, IBM Storage Scale serves as the backbone for IBM Fusion and the IBM Fusion HCI appliance, allowing organisations to swiftly and effectively deploy and manage Red Hat OpenShift apps and IBM Watsonx.
Content-Aware IBM Storage Scale
Unlock the hidden value of your enterprise data
Their chatbots and other AI helpers have limited economic relevance since the huge language models that underpin them are trained using very little enterprise data. This problem is solved by IBM Storage Scale’s content-aware storage features, which uncover the semantic meaning concealed in unstructured data to enable AI assistants to produce more intelligent responses on their own.
Unlock the benefits of performance, resilience and scalability
Improve performance for AI workloads
Construct a high-performance, globally networked infrastructure that can handle several workloads at once.
Unify data across hybrid cloud
Utilise a massively parallel file system to integrate many sources and locations by connecting and scaling data across on-premises and cloud environments.
Strengthen operational resilience
Keep systems with high levels of security operational and accessible by safeguarding data and boosting resilience against cyberattacks and outages.
Optimize storage for objects and containers
An S3 interface makes it easier to install and scale containerised workloads while providing high-performance access to file and object storage.
Enhance NVIDIA with IBM Storage Scale
Three easy-to-install configurations use GPU direct storage (GDS), NVIDIA DGX BasePOD and SuperPOD, and NVIDIA AI solutions.
Maximize performance for big data
Take full advantage of IBM Storage Scale’s Hadoop connector, which supports Apache Spark and Cloudera Analytics.
Take the next step with IBM
Data engineers may now effortlessly connect computation, data pipelines, and a vector database within the storage system for efficiency advantages, quicker access to data, and a shorter time-to-value with Storage Scale’s new content-aware features, which are widely available as of March 27, 2025.
