Building Unstructured Data Pipelines for Enterprise AI

As AI adoption accelerates, unstructured data — comprising over 90% of enterprise data — is key to differentiated, accurate AI. Yet less than 1% is used for GenAI today due to manual, fragmented processes.

Unlocking its value has not been easy, until now.

Join us for an exclusive webinar where we will show how IBM is solving these challenges by extending our data integration framework to unstructured data, with new capabilities for automated ingestion, transformation, and vectorization to power AI use cases.

You’ll learn:

Seamlessly ingest raw unstructured data from a variety of drag-and-drop connectors.

Leverage pre-built functional and quality operators to transform raw unstructured data into AI-ready data.

Populate supported vector databases with embeddings to be used for AI use cases.

Suresh Kumar

Sales Leader, Data Platform
IBM Asia Pacific

Suresh Kumar is a seasoned technology leader with over 30 years of global experience in Artificial Intelligence, Data Science, and Advanced Analytics. As Executive for Data Platform Sales at IBM Asia Pacific, he drives strategic AI adoption across industries, with a focus on enabling data monetization and business transformation. He has successfully bridged strategy and execution through design thinking, industry-specific use cases, and ecosystem collaboration. Suresh is recognized for his ability to translate emerging technologies into impactful business outcomes, helping organizations unlock the full potential of AI.

Suresh Kumar

Sales Leader, Data Platform
IBM Asia Pacific

Timothy CL Lam

Solution Engineer / AI Architect, Data & AI, ASEAN
IBM

Timothy CL Lam is a Solution Engineer / AI Architect at IBM. He designs sub millisecond GenAI systems for production—RAG/agents, vector search, and GPU accelerated inference. Formerly at Datastax, H2O.ai, Alteryx, and IBM, he holds certifications include AWS MLS, AWS SA Pro, DS201, Azure Data Engineer, and Databricks Spark Associate.

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