Most AI agents can query your data but can't understand your business. Building something to fix that.

Hi,

Observation from years in enterprise data:

Companies have better data infrastructure than ever. Cloud warehouses, modern pipelines, good BI tools. The plumbing is solid.

Then they plug in AI agents expecting transformation — and get disappointment.

The agent generates SQL. The SQL is correct. But the insight is wrong because the agent doesn't understand what the metrics actually mean in business context.

"Show me our best customers" → Agent picks highest revenue. But Finance meant highest margin. CS meant lowest churn risk. Sales meant biggest growth potential.

The agent didn't ask. It doesn't know.

The gap:

There's a missing layer between "access to data" and "understanding the business." Most AI agents skip it entirely and jump straight to automation.

What I'm building:

System of Record agents — AI that's grounded in the operational systems (CRM, ERP, billing) and trained to be an analyst first.

Before it automates anything, it learns:

• What do these metrics actually mean?
• How do they relate to each other?
• What's normal? What's an anomaly?
• What's the tribal knowledge that explains the exceptions?

Then — and only then — it starts automating.

Looking for:

• Feedback. Is this a real problem or am I in a bubble?
• Design partners. SMB or mid-market companies who live this pain.

Curious what this community thinks.