We built columnar data ops for AI agents — here's why and how

If you've built an AI agent that touches real enterprise data, you've probably hit this wall.

Your agent pulls 2,000 records from Salesforce. Now what? The model can't reliably filter, sort, or group 2,000 rows inside its context window. You don't want to dump all of it as raw JSON. And spinning up a Python runtime just to run a pandas filter feels like overkill for what should be a simple operation.

This is the problem we kept running into at DataGrout. So we built Frame.

What is Frame?

Frame is a suite of columnar data operations exposed as MCP tools — callable directly by any AI agent without a Python runtime, extra infrastructure, or round-trips to an analytics API.