Real time, AI-ready operational data

Power AI applications with real-time operational data, vector search and enterprise context in one open, scalable architecture

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Real-time data. Real edge.

Challenges

Many AI apps rely on static content, delayed pipelines or isolated systems. But the highest-value use cases depend on operational data that constantly changes—transactions, customer interactions, events, and app signals. When data is hard to access or slow to activate, AI stays stuck in pilots instead of supporting real-world decisions and actions.

Solution

watsonx.data helps organizations turn operational data into AI-ready context through open formats, fit-for-purpose engines and intelligent access across the enterprise data estate. For real-time workloads, that can include Astra DB, a Cassandra-based NoSQL engine designed for high-throughput reads and writes, low latency and always-on availability - delivered as a fully managed cloud service on AWS, Google Cloud, and Azure across 30+ regions.

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From data source to action in real time 01 Connect live operational data

Capture events, transactions, interactions and application signals as they happen. Stream event data through real-time processing platforms, while storing operational data directly in a high-performance NoSQL engine for low-latency access.

 02 Process, store and serve real-time data.

Continuously enrich and process live streams, then store and serve them through watsonx.data with a Cassandra-based NoSQL engine. Support high-throughput reads and writes while combining operational data with vector search and enterprise context.

 03 Power real-time applications and AI

Deliver real-time context to personalized experiences, IoT, banking, retail and supply chain use cases. Give teams the scale, security and openness needed to support decisions in milliseconds.

Why use watsonx.data for real-time AI?

Simpler, lower-cost operations without sacrifice

Reduce operational burden with a fully managed, enterprise-grade platform for NoSQL workloads. Eliminate much of the complexity of cluster management, patching and tuning so teams can focus on building and running applications instead of maintaining infrastructure. Lower TCO with centralized tooling, automation and more efficient resource utilization.
Fast, scalable, always-on performance

Build and scale real-time applications faster with familiar APIs, flexible data models and managed infrastructure. Support high-throughput workloads with low latency, elastic scalability, and global availability across clouds and regions—so teams can move from deployment to production quickly and confidently.
Unify data, act in real time, and govern with confidence.

Bring operational, analytical and vector data together in a fit-for-purpose architecture that supports real-time outcomes and AI-ready use cases. Enable low-latency access to live data without complex pipelines, while maintaining enterprise-grade security, governance and openness across the data estate.
Where real-time data creates AI advantage
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Personalized mobile experiences

Support recommendations, trips and orders, wallets, payments and rewards with always-on access to fast-changing operational data.
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Supply chain and logistics

Power fleet tracking, inventory visibility and shipment updates with real-time ingest and processing.
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Retail and digital commerce

Deliver responsive search, personalization and campaign experiences at scale with low latency and high throughput.
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Banking and fraud detection

Support payment processing, fraud detection and trading systems that depend on fast reads, writes and contextual retrieval.
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IoT and telemetry

Ingest and act on application signals, device events and network performance data in real time.
Resources

Proven for real-time, production-scale workloads

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How Bud Financial built a data intelligence platform
Bud Financial’s engineering team incorporated IBM technology into an architecture that enriches financial transactions in under five milliseconds with greater than 97% accuracy.
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How SupPlant turns live data into crop insights
SupPlant builds world’s first sensor-less smart irrigation solution.
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How Bay Point built secure AI for private markets
To accelerate clients’ ability to make critical financial decisions, Bay Point built Atlas, an AI-powered platform designed to let clients interact conversationally with their secure data rooms.
Take the next step

Discover how Astra DB in IBM watsonx.data can help you build real-time generative AI applications with a unified data platform. Start with a use case workshop, try Astra DB, or move from open-source Cassandra to a managed production model.

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