As AI agents become more powerful and widely adopted, enterprises face a new challenge: how to build them on a foundation of trustworthy, AI-ready data that includes both structured and unstructured data.
Unstructured data introduces new complexity for organizations already contending with large and growing volumes of data that is often distributed and disconnected, and from more information sources.
In this episode, Stephanie Valarezo, Program Director, Product, from IBM Data Integration, shares how organizations can simplify and scale the integration, access and governance of unstructured and structured data.
Explore how IBM is simplifying the enterprise data stack by empowering teams to integrate structured and unstructured data, using batch, real-time streaming, or replication techniques, while extending governance beyond the data layer to the AI agents themselves.
Whether you're modernizing legacy infrastructure, accelerating agent development, or building robust governance strategies, this session will give you a blueprint to:
- Unlock the value of unstructured data for enterprise-grade AI
- Accelerate data intelligence through built-in observability and governance
- Simplify your tech stack while improving trust and traceability in AI outputs
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