What Is Relyt AI-ready Data Cloud
With the exponential growth of data, the boundaries of enterprise data governance are expanding, leading to increasing challenges in data costs, privacy, and security. Concurrently, rapid advancements in technologies like generative AI are driving enterprises towards a new era of AI transformation and AI data business upgrades. In this context, based on typical enterprise data business scenarios and demand analysis, we believe there are two key requirements for enterprise-grade AI data infrastructure: First, it must be cost-effective and trustworthy for customers to adopt. Second, it must ensure optimal usage and maximize data value. The latter is more demanding, emphasizing AI-driven value creation and data collaboration to enable broader utilization of data value across the organization.b
Relyt AI-ready Data Cloud is committed to creating intelligent data solutions that realize this vision. By leveraging the advantages of unified analysis of structured and unstructured data, it continuously fortifies data integrity and security throughout the entire lifecycle of your business data. It outperforms competitors in AI analysis accuracy, multi-cloud capabilities, cost-effectiveness, hybrid workload support, and serverless architecture, and has been validated by AI platforms with millions of users worldwide, boosting efficiency and significantly cutting data management costs.
Adhering to a data-centric native cloud philosophy, Relyt AI-ready Data Cloud employs advanced data processing techniques like the integration of structured and unstructured data and hybrid search. This enables AI applications in rigorous data work fields, helping organizations build cost-effective, real-time, and precise AI-powered insights and data exploration services. It significantly lowers the barrier for data usage and provides new capabilities for data understanding and insights, leading to substantial efficiency improvements.
Relyt AI-ready Data Cloud leads the market in both performance and cost-effectiveness. It is cloud-agnostic and supports diverse workloads, including Retrieval-Augmented Generation (RAG), data warehouse, data lake, big data, and data science, all while ensuring a query success rate of at least 99.9%.