Turn scattered data into connected, trustworthy, controlled context your AI can use
Overview
Turn fragmented data into reliable AI outcomes—fast
Dispersed data, different definitions of the same data across systems and rising costs make it hard to scale AI. If the data lacks context and control at the moment it’s used, AI can’t deliver consistent, trustworthy results.
IBM® watsonx.data® makes data usable and trustworthy for AI on Day 1— supporting all your AI and BI workloads without replatforming
Features
Designed for trustworthy, scalable data
Access and query data across cloud and on‑prem environments without moving or duplicating it. This gives teams a complete, connected view of data across systems so AI can use the right data with the right context while meeting regulatory and operational needs.
Run each AI and analytics workload on the most efficient engine, preventing overprovisioning and improving performance. This helps ensure context is delivered quickly and efficiently to those workloads, helping keep costs predictable as usage scales.
Apply consistent access controls, policies and lineage across all data and workloads. This helps ensure AI uses data that’s not only trusted but also governed at the moment it’s used—reducing risk and increasing confidence in outcomes.
Use an open, standards-based foundation that works with your existing technology stack—supporting new tools and workloads as your AI needs grow. This eases connecting and extending context across your data ecosystem without locking into proprietary formats.
See watsonx.data in action
Move from first use case to real AI impact—fast. Get started quickly, prove value early and scale what you’ve built across your organization without complex setup. See how teams turn their data into the context AI needs to deliver measurable results—and expand AI with confidence.
Use cases
AI-powered enterprise search with OpenRAG
Unlock business data
Real-time access to AI-ready data
Multi-engine execution that’s fit for purpose
Unlock value from your data
Deploy the power of agentic AI with OpenRAG to deliver context-rich AI outcomes. Build on open-source foundations to launch your RAG solution in minutes, moving quickly from pilot to productivity.
Enable AI applications, analytics and BI tools to work with connected, context‑rich, governed data across databases, data lakes, documents and object storage to yield consistent and explainable results.
Run AI and analytics workloads on the engines best suited to their performance and cost needs, avoiding one‑size‑fits‑all platforms and optimizing price performance as workloads scale.
Case studies
Real clients, real results
Real clients, real results
Resolving help desk tickets faster with AI-ready data
CrushBank increased its tickets resolved per day by 40%, using watsonx.data as a central, governed store for structured and unstructured data. This enabled their AI system to retrieve accurate, customer-specific information quickly, cutting average resolution time and improving first-call resolution rates.
More ways to buy
Resources
The data leader’s guide to AI-ready data
Turning Data Strategy into AI Impact
Poor data quality is a compounding threat
Optimize your most valuable AI asset—your data
Insights and supporting materials
Footnotes
1. Millions Lost In 2023 Due To Poor Data Quality, Potential For Billions To Be Lost With AI Without Intervention, Forrester, 31 July 2024.