The Architecture Behind Trustworthy Enterprise AI Agents

Building an AI agent your business trusts comes down to what you feed it. Raw data isn't enough. It needs the layer that makes data mean something: how your company defines its metrics, the judgment your analysts apply without thinking, the norms for what's allowed. It's the foundation a trustworthy agent runs on, and the part most teams build last.

Anugraha Sinha (Director, GenerativeAI, Tredence) and Austin Kronz (AI and Data Strategy, Atlan) map the reference architecture on screen: setting up the right foundations, where that context sits, how definitions and access get set, and what holds up at enterprise scale. Grounded in how Tredence has built this across the world's largest companies, including what breaks and what lasts.

Then a live before-and-after: the same agent, the same question, answered once with thin context and once with a governed context layer.