VAST Data Tackles Enterprise AI Bottlenecks
Data infrastructure provider VAST Data has unveiled significant enhancements to its platform, aiming to assist organizations struggle to scale their artificial intelligence deployments amid growing demands for faster data processing and improved security measures.
According to VAST Data, the updated platform introduces three key capabilities: trillion-scale vector search and retrieval, serverless triggers and functions, and fine-grained access control mechanisms.
The company's vector database now supports trillion-vector scale with constant-time search capabilities, a feature VAST claims makes it both "possible and practical" to index all enterprise data for availability to AI workflows at any scale.
With AI-powered Similarity search for real-time analytics and discovery, organizations can turn real-time data into AI-driven decisions by automatically embedding vectors for search and retrieval.
Additionally, the platform's DataEngine introduces event-driven automation designed to create realtime workflows without requiring background ETL tools. This system can embed and serve context to AI applications instantaneously, potentially removing barriers to implementing Retrieval Augmented Generation (RAG) in enterprise environments.
On the security front, VAST has implemented advanced row- and column-level permissions to ensure compliance and governance for analytics and AI workloads, while unifying permissions across both raw data and vector representations.
"Only two kinds of companies exist today: those becoming AI-driven organizations, and those approaching irrelevance," said Jeff Denworth, Co-Founder at VAST Data.
“In order to thrive in the AI era, enterprises need instant AI insights, enterprise-grade security, and limitless scalability – without worrying about managing fragmented tools or data infrastructure. The VAST InsightEngine is the only market’s first and only solution able to securely ingest, process, and retrieve all enterprise data – files, objects, tables, and streams – in realtime to make enterprise data instantly usable for accurate AI-driven decision making.”