Hi Data & AI Pros,

Most AI failures are not model failures.

Stale snapshots. Missing context. Source codes your model cannot interpret properly. If your data pipeline was not built for AI, your agents will hallucinate, and no prompt will fix it.

I have had this conversation with a lot of data leaders this year. The pattern repeats. Teams spend months on the model layer while the real failure sits 2 steps upstream, in how data is pulled, joined, validated, and versioned.

CData Sync was built to fix exactly that. It pulls from hundreds of sources, replicates in real time with CDC, and delivers clean, version controlled data your AI layer can actually rely on.

Not AI ready yet? That is the normal starting point, and it is fixable.

Live Demo: Why Your AI Agent Gives Wrong Answers (And How to Fix the Data Layer)

September 9, 10am ET. 45 minutes. Free.

In 45 minutes the CData team shows what AI ready data means technically, what it looks like in practice, and how to build a pipeline that produces it, live.

What you will leave with:

- The 3 data layer failures that cause AI agents to hallucinate
- How to assemble cross source context in a single pipeline
- How to enforce a data quality gate before the AI layer
- How to keep your data pipeline version controlled and auditable

 Want to try it against your own stack first?

If you are the person who gets pulled into the room when the agent returns the wrong number, this session is aimed at you.

See you on September 9.

I have a new favourite word from Glean:GO 2026. "Botsitting" I was sitting in the front row when it landed, and the room reacted the way you react when someone names a thing you have been doing for months without a word for it. Finding the file. Pasting the background. Connecting the tool. Correcting the answer. Explaining the same context again the next morning. We have all been calling that "using AI." It is closer to babysitting.
 
And here is the part that matters. Botsitting is not a model problem. It is a context problem. The model has no idea who your customers are, what your team decided last week, or which of those 4 documents is the real one.
 
That single idea sits underneath everything Glean announced today.
 
Glean Tau, a desktop workspace that combines enterprise context with your local files, applications, code and the latest models. It can plan, execute, review, recover and act. Recover is the word I would circle. Executing a plan is table stakes. Recovering from a failed step without a human stepping in is the line between a tool you supervise and a teammate you trust.
 
The benchmark everyone will screenshot. Against Claude Cowork, Glean's response was preferred 78 percent of the time at $0.58 per query versus $2.98. An 81 percent token cost saving. More context does not have to mean more cost when the context is already indexed instead of rebuilt on every request. It is a vendor run benchmark, so treat it as a reason to test on your own queries rather than a verdict.
 
Context that stops getting rebuilt. People, content, processes, customers, infrastructure, all permission aware, so the AI knows what matters, what is connected, what it can access and what happens next.
 
Control over the economics. Usage visibility, auto routing across efficient, balanced and frontier models, and usage controls across users, teams and models. Model choice just became a budget decision instead of an engineering preference.
 
Glean AI Gateway, one common layer for models, context, memory, MCP and security, so all of this does not become sprawl nobody can govern.
 
Team chat, where multiple people work with Glean in 1 shared thread and every response still respects individual permissions.
 
Plus Transform, proactive task management, interactive dashboards and context aware threat detection, which flags risky agent behaviour even when every individual action was permitted.
 
The thread through all of it: models are becoming interchangeable, enterprise understanding is not.
 
We are moving from AI that answers questions to AI that understands the business and gets work done.
 
Swipe through the carousel for the full breakdown. Then tell me which one you would actually put to work on Monday.

Ravit Jain
Founder & Host of The Ravit Show
The Ravit Show

In partnership with the CData team.