You've been in that room. The board meeting where the CEO asks a simple question about revenue. Sales pulls from Salesforce. Finance pulls from NetSuite. Ops pulls from a spreadsheet someone emailed last Tuesday.
Three numbers. None of them match. Everyone has a number. Nobody has the same number. You spend the next three weeks reconciling instead of deciding — and by the time you have an answer, the decision window has closed.
Your data engineering team has become the bottleneck for every strategic question in the organization. Marketing wants campaign attribution data — ticket filed, two-week wait. Product wants churn correlation — ticket filed, three-week wait. Meanwhile, executives make decisions on stale dashboards because fresh data requires a sprint of engineering effort.
You have a three-week ticket queue for a query that should take three seconds. Permissions are managed tool-by-tool, so there's no unified view of who can access what.
And the 70% transformation failure rate that a16z cites? You're living it. Your "data transformation initiative" from eighteen months ago still hasn't delivered what was promised.
Gartner reports that poor data quality costs the average organization $12.9 million per year — and the indirect cost of eroded decision-making confidence is higher.
Your data team isn't building anything. They're answering questions. Every day you don't fix this, the queue gets longer, the dashboards get staler, and the shadow analytics stacks multiply.
How many more quarters of stale dashboards before someone builds their own rogue data pipeline? They probably already have.
A unified data catalog with natural language querying and centralized access controls. Business users query data directly — no tickets, no queues, no three-week waits.
Your data engineering team shifts from answering questions to building infrastructure. The system of action layer that a16z describes — the one that sits on top of your systems of record and actually lets people do work.
30 minutes. We'll map what's broken, show you what to build first, and connect Agent Lake to your stack.
Talk About Mid-Market30 minutes. We'll map your current data landscape, identify what to build first, and show you how Agent Lake connects to your stack. No pitch deck. No commitment.