Doris Summit 2026Day 1 · Keynotes

Talk to Your Data: Building Next-Generation Enterprise AI Agents

Owen Xiao · VeloDB

About this session

Agentic Analytics is reshaping how enterprises interact with data, built on three foundational pillars: the Analytics Agent, the Context Layer, and the Analytical Database. First, the Analytics Agent: Web-Native and Enterprise-Ready. Web-based Analytics Agents are better suited for enterprise adoption than desktop agents, offering native support for multi-user collaboration, centralized governance, fine-grained access control, and auditing. Second, the Context Layer: Open, Markdown-Based Knowledge. A Markdown-based filesystem approach provides a unified knowledge foundation, where schemas, semantic metrics, business rules, and documentation are organized as human-readable, Git-versionable, and LLM-friendly files, accessible to agents through MCP servers and APIs. Third, the Analytical Database: Serverless and Elastic. The bursty, highly concurrent, and unpredictable query workloads generated by AI agents call for serverless analytical databases like Apache Doris, with elastic scaling, rapid scale-out, and pay-as-you-go economics. Together, these three pillars establish a complete Agentic Analytics architecture, connecting natural-language interactions with business context and scalable analytical execution to deliver trusted, actionable insights.