Pasting a spreadsheet into ChatGPT and asking “what was May’s margin?” is tempting: the answer comes in seconds, written with confidence. The problem shows up in the board meeting, when someone asks “where did that number come from?” — and the only honest answer is “the AI said so.”
Redijo starts from that question. The answer exists only if the source exists, and every figure carries back the file, the tab, and the range behind it.
A fluent answer is not a proof
A general AI chat reads the text and drafts something that sounds right. Sometimes the figure is correct; sometimes it’s a confident hallucination — and you only find out by checking by hand. The vendors themselves warn the model can make mistakes. In Redijo, calculation and comparison are deterministic, kept off the AI’s path: the model never computes the number, it only drafts the prose around it. You don’t trust — you review.
Permission at synthesis time
In a shared chat there is no per-fragment permission: whatever enters the conversation is visible to anyone with access to it, and on consumer tiers your data can feed model training. Redijo enforces each fragment’s permission at the moment the answer is composed — what you can’t see never enters, not even hidden inside an aggregate total. That’s our moat.
Where generic AI has the edge
In fairness: for drafting an email, brainstorming an idea, or reasoning over text with zero setup, ChatGPT and Claude are excellent — and Redijo doesn’t try to replace that. In fact, Redijo exposes an MCP server so you can keep using your preferred model, just through an audited seam, with permission enforced and a full audit trail.
Your files are hosted with international-transfer safeguards — GDPR-grade controls by architecture.