Data Integration

Schema drift can break pipelines and delay data products. Iceberg and Nexla keep Medallion workflows stable, audit-ready, and engine-agnostic.

Learn how to transform your data into AI-ready assets. Understand the components of AI-ready data and how Nexla’s data product capabilities empower your AI initiatives.

In the News: Nexla CTO Amey Desai shares how Nexla supports MCP, enabling secure, AI-native data integration through Nexsets and agentic orchestration without compromising standards.

By combining an intelligent orchestration layer with a robust runtime engine, organizations can scale their AI integration capabilities while maintaining operational control.

In the News: Nexla CEO Saket Saurabh explains how data variety—differences in formats, sources, and structures—is a major reason AI initiatives fail to scale. You’ll learn about modern strategies like virtual data products and agentic integration.

Success now hinges on how well businesses share data beyond their walls. Seamless intercompany data flow fuels smarter decisions, faster collaboration, and real growth. In this new era, connection is the key to competitiveness.

In the News: Nexla landed a spot on the DBTA 100 2025, a list recognizing the top companies shaping the future of data. This year’s list highlights leaders driving innovation in AI, data integration, and digital trust.

In the News: Saket Saurabh, CEO and Co-founder of Nexla, joins Jennifer Pierce on Innovators Journey to talk about how Nexla continues to push the boundaries of AI and technology.

Success now hinges on how well businesses share data beyond their walls. Seamless intercompany data flow fuels smarter decisions, faster collaboration, and real growth. In this new era, connection is the key to competitiveness.

If history is any guide, Fivetran’s acquisition of Census would likely follow the same bundling model we’ve seen with HVR. Integration might not follow anytime soon.

In the News: Co-founder and CEO at Nexla, discusses how data engineering is evolving to support generative AI—highlighting data quality, governance, and human-in-the-loop workflows for building trustworthy AI systems.

By combining an intelligent orchestration layer with a robust runtime engine, organizations can scale their AI integration capabilities while maintaining operational control.