Every new question is a report request. AI can let your SIS customers ask it themselves.

The report queue is the real problem

Which cohort is slipping, which program fills last, where learners drop: each new question waits for someone to build a report. Your customers want the answer inside the product they already pay for.

A generic chatbot cannot help, because term, cohort, active and at-risk mean something different at every institution, and records data carries the strictest terms in the market.

What good looks like

1. 01

   Plain-English questions, checkable answers

   The question becomes a query over your reporting database or warehouse. The answer is a table or chart, and the query is visible to anyone who wants to check it.

2. 02

   Each institution's own definitions

   A semantic layer holds each institution's terms, so the same word returns the right numbers everywhere.

3. 03

   Permissions inherited, not reinvented

   Answers come only from rows the user can already see in your product, and institutions stay isolated from each other.

4. 04

   Summaries for program leads

   A short weekly read-out per program, written from live data, for a person to act on.

How to prove it before you ship it

• Collect twenty real questions your customers ask today.
• Run them against a de-identified copy of your schema and check each answer against a reviewed result.
• Track the share that match, and fix definitions before you widen access.
• Keep an audit log of every question, query and answer.