The Fifth Elephant 2026 Annual Conference

Describe your session in 2 paragraphs

Everyone has seen how AI transformed software engineering. Tools like Claude Code and Codex work because code comes with rich context—source control, dependency graphs, reviews, tests, and execution history. Enterprise data, however, lacks an equivalent foundation. AI agents are expected to answer questions, generate SQL, understand business metrics, and automate workflows while operating on fragmented metadata, inconsistent business definitions, and disconnected systems. Bigger models alone don’t solve this problem.

In this session, we’ll explore the concept of an Open Context Layer—a new architectural layer that gives AI agents a shared understanding of enterprise data through Context, Semantics, and Memory. Using OpenMetadata 2.0 as an open-source case study, we’ll walk through how unified metadata graphs, ontology-driven semantics, and organizational memory can make AI systems more accurate, explainable, and reliable. We’ll also discuss the open standards behind this architecture, including knowledge graphs, MCP, OpenLineage, and RDF, and share practical lessons from building these capabilities in production.

1–2 takeaways from your session

• Understand why enterprise AI systems fail even with state-of-the-art LLMs, and why context—not model size—is becoming the critical differentiator.
• Learn practical architectural patterns for building an Open Context Layer using metadata, semantics, knowledge graphs, and organizational memory that any AI platform can leverage.

Which audiences will benefit?

This session is intended for:

• Data Engineers
• Data Platform Engineers
• AI/ML Engineers
• Analytics Engineers
• Data Architects
• Engineering Managers and Technical Leaders building AI-powered data platforms

Speaker bio

Mayur Singal is a Lead Integrations Engineer at Collate and an active contributor to the OpenMetadata project. He works on metadata ingestion, lineage extraction, and integrations across more than 130 data platforms, helping organizations build AI-ready data ecosystems. His work focuses on open standards, metadata systems, and building the infrastructure that enables reliable AI applications over enterprise data.

Draft slides

https://docs.google.com/presentation/d/1vSnNV6MaqEDjx9kE5uBvCy8zuBatTyIDVZAjove7RoA/edit?slide=id.g3e26a7a2d57_0_7013#slide=id.g3e26a7a2d57_0_7013