Products
Modular AI surfaces built for every layer of allied-health education. Each one is deployed and running across the campus network today.
Predicts student outcomes against the concept knowledge graph, surfaces at-risk learners early, and recommends the specific intervention rather than a generic alert.
Turns uploaded course material into structured textbooks and personalised learning plans through a three-pass pipeline, then launches them inside Canvas over LTI 1.3 with grade passback.
Scores resumes on a 0–100 rubric, runs AI mock interviews against a four-category weighted rubric, verifies external application proof, and matches students to externship and job openings.
An edge camera fleet streams the bench to a realtime voice model with frames injected, so the agent can answer questions about what it is actually looking at. Recordings render and publish automatically.
Agents for transcription, extraction, tagging, vision, and assessment run on dedicated queues, with structured output validated before anything reaches a student record.
A unified layer that ingests, normalises, and resolves entities across every campus system, giving agents one governed source of truth instead of a dozen disconnected exports.
We will walk you through any of these surfaces against a live campus.