Build private AI agents on your company data – for real workflows(vdf.ai)

Which company data sources connect out of the box? Asking because student SIS data lives in PowerSchool and exports are a nightmare.

Agreed, the privacy story matters less than whether the agent can actually navigate messy internal data. We ran a study with 14 knowledge workers using a private agent over Confluence and SharePoint, and the biggest failure mode was stale documents being treated as ground truth.

private rag pilots die when nobody owns the data freshness pipeline

Privacy claims fall apart the moment someone uploads a deposition PDF to a "private" workspace that quietly indexes through a third-party embedding API. Spent two weeks last fall mapping where our matter documents actually flowed across one of these tools and found four hops the vendor never mentioned in their SOC 2.

Built one of these for a 12-person boutique agency last month. Pointed it at their Dropbox of past pitch decks and client briefs, and the account team went from spending two days on a kickoff doc to about forty minutes. The catch nobody mentions: I spent the first week just renaming folders and killing duplicate "FINAL_v3" files so the retrieval didn't choke. Cleanup work isn't glamorous but it was 80% of the project.

Half my "real workflows" turned out to be three SQL queries someone wrapped in a chat box.

Most "private agents on company data" demos fall over the moment they hit a SharePoint with 200k docs where half the access-control lists are stale, so the agent confidently surfaces a salary sheet HR forgot to lock down. The hard part was never the model or the workflow; it is that your permissions graph is a lie and the agent is the first thing that reads all of it at once.