Why Data Context Matters: Inside Atlassian’s Teamwork Graph and AI Agents
From The Ravit Show by Ravit Jain
June 8, 2026 · 10 min
About this episode
The episode explores the significance of data context in AI, featuring insights from Atlassian's Head of AI Product, Jamil Valliani, on their innovative Teamwork Graph.
Most AI tools are still just indexing documents. The Teamwork Graph has 150 billion connections. That difference is the whole game. I sat down with Jamil Valliani, the Head of AI Product at Atlassian, during Team '26 on The Ravit Show to understand why they are betting the next decade on this approach. Twenty years in Search before this role. Long before vector databases were trendy. Long before RAG was an acronym.A few things we got into:What the Teamwork Graph actually is. Why this architectural choice separates Atlassian's AI from everything else in the market.150 billion connections vs document indexing. Most enterprise AI tools search your text. This connects people, work, decisions, and outcomes across systems. The gap is bigger than I realized.Why connected data wins on accuracy. Atlassian's internal benchmark: 44% more accurate results using 48% fewer tokens. We broke down what is actually happening under the hood.A Search veteran's read on this moment. What makes this AI shift different from every other one. The most grounded take I heard at any conference this year.The line that stayed with me: in the next era of work, the company with the best context will win. Not the…
People in this episode
Host: Ravit Jain
Guest: Jamil Valliani
Topics covered
- AI
- data context
- Teamwork Graph
- enterprise AI
- accuracy
- search
Keywords
- data context
- AI tools
- Teamwork Graph
- Atlassian
- accuracy
- document indexing
- enterprise AI
- search
Mentioned in this episode
Organizations: Atlassian
Books & works: The Ravit Show
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