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We have watched this play out across enterprise deployment after enterprise deployment.The conversation starts with mode...
07/13/2026

We have watched this play out across enterprise deployment after enterprise deployment.
The conversation starts with model capability.

Then you look at the actual deployment.

And the agents are asking questions about data they have never been given access to.

The model is the final variable.
The data layer is the constraint.

Teams solving that layer first are reaching production.

Teams skipping it are rebuilding their demos six months later and calling it a change management problem.

The AI race will be won by the organizations that solve governed data infrastructure first.

The window for owning that layer at mid-market scale is 12 to 18 months.

What are you seeing on the deployments you are working with?

MCP is becoming the standard protocol for agent-to-data connectivity.This matters more than most enterprise teams realiz...
07/10/2026

MCP is becoming the standard protocol for agent-to-data connectivity.

This matters more than most enterprise teams realize right now.

MCP gives AI agents a standardized way to reference governed, trusted operational data at runtime.

It is the missing protocol layer between enterprise systems and the agents built to reason over them.

The infrastructure layer that governs what agents can see and trust is being defined now.

That creates a narrow strategic window.
→ 12 to 18 months
→ Protocol standardization is happening now
→ Microsoft is accelerating Copilot distribution
→ The governed data infrastructure layer is becoming one of the most strategic surfaces in enterprise AI

The partner who owns it owns the deployment relationship.

This is the shift we are building for.
What questions are you hearing from clients about MCP and enterprise agent connectivity?

07/09/2026

We keep running into the same conversation with enterprise teams.

The demo works.
Production stalls.

The root cause shifts depending on who you ask.

However, patterns repeat across deployments.

So we want to ask:
What is the biggest blocker you are seeing right now in enterprise AI deployment?

Enterprise AI is stalling.The models are improving every quarter.Enterprise production adoption rates are sitting at 3 t...
07/09/2026

Enterprise AI is stalling.

The models are improving every quarter.

Enterprise production adoption rates are sitting at 3 to 5 percent by partner reports.

But the gap is not the model.
It is the data layer underneath it.

→ Operational data lives across disconnected ERP, CRM, WMS, finance, and eCommerce systems.

→ These systems were never unified, standardized, or governed for AI consumption.

→ When a Copilot or CORBI agent tries to reason over live business data, it hits the same wall every time.

That wall is fragmented data.

No address system.
No normalization.
No access governance in place.

The bottleneck is infrastructure.

The teams that solve the data layer first are the ones reaching production.

We see this pattern across enterprise deployments of every size and vertical.

What is the biggest infrastructure gap you are running into on enterprise AI projects?

06/19/2026

If you could automate one thing at your company starting Monday, what would it be?

We ask this a lot in discovery calls and the answers are always interesting.

Drop it in the comments.

The most common pushback I hear from investors: "Will Microsoft just build this themselves?" Microsoft sells Copilot li...
06/17/2026

The most common pushback I hear from investors: "Will Microsoft just build this themselves?"

Microsoft sells Copilot licenses. Their revenue motion depends on partners handling the data complexity underneath. Those partners need a purpose-built infrastructure layer.

The moat here is we built the thing Microsoft's distribution channel depends on. That is a different defensibility argument from category competition with the platform itself.

If this distinction matters to you, DM me. I would rather spend 20 minutes on the hard questions than send a deck.

06/16/2026

Central AI works across cloud and on-premise systems.

That matters more than people realize. A lot of mid-market companies are not fully in the cloud yet, and not fully integrated. They should not have to be to get the benefits of automation.

Meet businesses where they are. That is the whole idea.

06/15/2026

A lot of companies are asking "how do we use AI?"

The better question is "is our data ready for AI?"

Fragmented systems. Duplicate records. Manual data entry. These do not just slow you down today. They will hold you back from everything AI can do for your business tomorrow.

06/12/2026

We talk to a lot of operations teams.

The problem is almost never that they picked the wrong software.

It is that the software they implemented does not talk to the other software that exists in the ecosystem.

Lack of Integration is the unsexy problem that quietly kills productivity at a lot of great companies.

The window for owning the MCP infrastructure layer is compressing. As companies accelerate Copilot distribution and MCP ...
06/10/2026

The window for owning the MCP infrastructure layer is compressing.

As companies accelerate Copilot distribution and MCP becomes standard protocol, the governed data infrastructure layer becomes the most competed surface in enterprise AI.

Investors who engage this layer now will be ahead of the premium acquisition phase. The normalization and governance moat requires deep, hands-on history with the actual enterprise systems that agents need to reference. Building that credibly takes years.

12 to 18 months from now, this question will be settled.

Curious whether other investors tracking the MCP stack are seeing the same compression.

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