---
title: "Atlan + Tredence: The Architecture Behind Trustworthy Enterprise AI Agents"
url: "https://atlan.com/live-demo-series-atlan-tredence-ai-agent-architecture/"
description: "Tredence has built AI agents inside the world's largest enterprises. Watch them and Atlan map the trustworthy AI agent architecture live. Aug 12, 11 AM ET."
---

> Atlan is hosting Context Conference, bringing together the leaders and builders at the frontier of giving AI the context it needs to understand their business. It runs online on October 28, 2026, from 11:00 AM to 2:00 PM ET. Atlan co-founder Prukalpa Sankar opens and closes the day. Leaders from AstraZeneca, BNY and Verizon share why they invest in context and what they get from it. Registrants get early access to The AI Context Gap, a new study from MIT Technology Review Insights. Register: https://atlan.com/context-conference/

**Atlan in Action live demo with Tredence, on demand: The Architecture Behind Trustworthy Enterprise AI Agents.** Tredence has built AI agents inside some of the world's largest enterprises. Tredence and Atlan map the architecture that makes those agents trustworthy: what the right foundation looks like, and where the context layer fits. For teams building enterprise AI agents.

**Watch:** the full session is available on demand (45 min); fill the form on the page to watch the recording: [https://atlan.com/live-demo-series-atlan-tredence-ai-agent-architecture/](https://atlan.com/live-demo-series-atlan-tredence-ai-agent-architecture/). More demos: [https://atlan.com/live-demo-series/](https://atlan.com/live-demo-series/).

## About this session

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 and Austin Kronz 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.

## Speakers

- Austin Kronz, AI and Data Strategy, Atlan
- Anugraha Sinha, Director, GenerativeAI, Tredence

## What you'll see

1. **How to think about building an agent you can trust.** The mental model experienced teams use before the first line of code: how they frame the problem, what they set up first, and the questions worth answering before you build.
2. **What Tredence has learned building this at scale.** The architecture patterns Tredence sees hold up across enterprise agent projects, what teams get wrong before they've shipped anything, and what breaks the moment real users start depending on the answers.
3. **What the right foundation looks like.** The reference architecture for a trustworthy AI agent, mapped on screen: where the context layer sits between your data and the model, how definitions and access get set, and the layer most teams skip on their way to a demo.
4. **The difference, live.** One agent, one question, answered twice: once with thin context, once with a governed context layer. A direct side-by-side on how much the foundation changes what the agent gets right.

## Customers

Trusted by 500+ AI-forward enterprises. Customers shown: Mastercard, HubSpot, Zoom, Dropbox, Autodesk, Nasdaq, Fox, GitLab, Unilever, Workday, Elastic, NHS, Affirm, General Motors, easyJet, Medtronic, New York Life, Grainger.

Customer videos ("The only proven way to create context"): DigiKey: Context Readiness (Sridher Arumugham) / CME Group: Context at Speed (Kiran Panja) / Mastercard: Context by Design (Andrew Reiskind) / Virgin Media O2: Context for All (Mauro Flores).