--- title: "Atlan Activate 2026: The Context Layer, Live." url: "https://atlan.com/activate/" description: "Join us as we unveil Atlan's newest chapter with product launches like Context Studio and AI Data Stewards." keywords: "Atlan Activate 2026, context layer, AI agents, context studio, AI data stewards, data quality studio, metadata lakehouse, MCP server, app framework, data governance, metadata management, context-driven AI, agentic governance, semantic models for AI, context products, AI-ready data, enterprise AI context, data catalog AI, Atlan product launch" --- > 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 Activate 2026, "The Context Layer, Live.", is Atlan's online product launch event (April 29, 2026, 11:00 AM to 12:30 PM ET, free, per the page's event schema). "Everyone's talking about the context layer. Nobody's shown you how to build one. Until now." The event is over; the recording is available: [Watch Recording](https://atlan.com/context-layer-demo/). What the session shows (hero list): - Watch AI create and maintain context automatically - Bootstrap context repositories for AI - Find & fix context gaps with simulations - Deploy context to any AI agent - See AI agents access context at scale - Observe interactions & improve context continuously ## The context layer is the most viral thing in 2026 "Well, after Openclaw." Context graphs went viral on X. Gartner called the context layer "the most important enterprise asset of the AI era." Karpathy wrote about context engineering. And overnight, every vendor became a "context company": foundation models, semantic layer vendors, knowledge graph companies, data warehouse companies, data integration companies, systems of record. The questions nobody's answering: - Is a context layer just a data catalog with AI features? - Do I need a knowledge graph, an ontology, a semantic layer, or all three? - How do I go from not knowing where my data lives and 500,000 undocumented assets to a working context layer without a 2-year project? - What does a context layer actually look like in production? - Who owns the context layer: the data team, the AI team, or the platform team? ## Product launches - **The Context Engineering Studio**: AI bootstraps 90% of your context layer. Your team adds the rest (business logic, edge cases, knowledge only they have). Simulate. Refine. Ship to any execution engine. - **Context Agents**: 9-12 months of enrichment work, done in minutes. Nine AI agents solve the cold start problem the moment you ask. - **Traces & Observation Loops**: Agents get things wrong. Traces show exactly where. Corrections flow back into context automatically. Smarter every week, without touching the model. ## Agenda ### Enterprise Data Graph Where does context actually come from? The living map, and what happens when AI agents finally have access to it. - **Context Agents, Live**: nine AI agents that write, maintain, and continuously evolve the documentation your team never did. Watch them outperform humans on documentation quality. - **Conversational Search, Reimagined**: ask questions about your context and learn what it takes to build accurate, performant context retrieval. - **The Context Ecosystem, Connected**: the Enterprise Data Graph is the backbone of the context ecosystem. Partners have built on it. AI systems read from it. ### Context Engineering Studio Engineer, test, and ship the enterprise knowledge that makes AI agents reliable. - **Bootstrap Context Repos**: AI bootstraps 90% from SQL patterns, lineage, and usage signals. Domain experts add the last 10%: business logic, exceptions, tribal knowledge. Versioned. Bounded. Portable to any execution engine. - **Simulate & Test Context**: turn your BI dashboards into an automated eval suite. When a test fails, the studio pinpoints what's missing and suggests a fix. Know when your agent is ready before your users find out it isn't. - **Observe & Improve**: every production interaction is a signal. Corrections become context updates. Correct answers become regression tests. Agents get more reliable every week, without the model changing. ### Context Lakehouse The first knowledge architecture built for a world where AI is the primary producer and consumer of context. - **Map the Knowledge Graph**: domains, semantic models, lineage, policies, quality scores, all connected and live. What changes when an agent knows what an asset means, where it came from, and whether it can be trusted. - **Own Your Intellectual Property**: context is IP. The knowledge your teams have built about your data belongs to your organization: store, version, and own it on open standards. - **Deploy Context to Agents**: MCP for governed queries. A2A so agents write context back. SQL for analytics. Context moving from question to answer, in production. ### Introducing the AI Context Ecosystem The entire AI context ecosystem, together for the first time. - **App Framework**: how developers, partners, and customers can build connectors and apps using Atlan's App SDK. - **Context Layer Partners**: partners across observability, orchestration, security, governance, and business systems forming the AI Context Ecosystem. - **Policy Context Layer**: partner demos from Cyera and Immuta on how they built their own apps on Atlan to connect the Policy Context Layer. ## This is for you if - You're a CDO, VP Data, VP AI, or platform lead trying to figure out who owns context in your organization. - You have 500,000+ data assets and no idea how to document them for AI without a multi-year project. - You're building AI agents and they keep getting things wrong, not because the data is bad, but because the agent doesn't know what the data means. - You've heard "context layer" from every vendor this year and still can't picture what one actually looks like. - You survived the pilot, but now you need to scale to 10 agents, and nothing is shared. ## Trusted by the world's leading AI native enterprises Customers shown: Mastercard, HubSpot, Zoom, Dropbox, GitLab, CMA CGM, Fox Corporation, PPG, Ralph Lauren, Virgin Media O2, Riot Games, Workday, Elastic, HP, Affirm, General Motors, Nasdaq, Medtronic, New York Life, Grainger. Also shown near the closing CTA: Autodesk, HelloFresh, Cisco, Plaid. Analyst recognition shown: Forrester Wave Leader 2025 and Customer Favorite 2025 (Data Governance Solutions), Gartner Magic Quadrant Leader for Metadata Management 2025 and for Data & Analytics Governance 2026. [Watch the Activate 2026 recording](https://atlan.com/context-layer-demo/)