Joanna Zouhour

Despite decades of perfecting structured data pipelines, 80% of enterprise knowledge remains functionally invisible, trapped in PDFs, images, and office documents. Traditionally, Intelligent Document Processing (IDP) has been a fragmented nightmare. Before the era of Generative AI, organizations were forced to rely on disconnected NLP and computer vision APIs that were outside of their primary data platforms.

Data engineers are increasingly focused on one core problem: using AI to improve ETL and build reliable, production-grade pipelines without introducing new complexity. They need AI that actually delivers, streamlining workflows without adding disconnected tools or stripping away context. Databricks Lakeflow brings a unified data engineering platform with embedded and secure AI that automates your entire data processing, unlocks more insights, and supports a broader range of business problems.

Data engineers are increasingly frustrated with the number of disjointed tools and solutions they need to build production-ready pipelines. Without a centralized data intelligence platform or unified governance, teams deal with many issues, including: Inefficient performance and long starts Disjointed UI and constant context-switching Lack of granular security and control Complex CI/CD Limited data lineage visibility etc. The result? Slower teams and less trust in your data.