The operating model of your institution
We unify all your institutional data, logic, and actions into a single model that powers all of your operations.
Ontology
The central system that enables AI operations at scale.
The ontology is the operating model of your institution. It encodes the data underneath your institution, the logic that governs how it works, and the actions that can be taken.
A single source of truthEvery agent, app, and model can reason about and act on a single source of truth.
Ontologized data
The entities your institution runs on — students, courses, grants, holds, buildings, payments — with every property and relationship, unified in one place.
- Every entity with its properties and its relationships to every other entity it touches.
- The ground truth of your institution, unified in one place.
Logic
The rules that govern how your institution operates — federal, state, institutional.
- Encoded once, executed everywhere they apply.
- Explicit, auditable, versioned.
Actions
The levers that can be pulled — release a hold, assign a room, approve an award, update a record. Every action wired to the source system where it actually happens.
Data
Every system.
Every method.
No exceptions.
Your ontology is only as real as the data beneath it. We ingest from every system you run, by whatever method it takes. Our agents keep everything normalized, connected, and current without brittle pipelines in the middle.
Universal
Every major campus system
SIS (Banner, Colleague, Jenzabar, Workday Student), ERP (Workday, PeopleSoft), CRM (Slate, Salesforce), LMS (Canvas, Blackboard), HR, Facilities, Housing, Health, Dining
Every method
ODBC, API, SFTP, flat files, browser agents against legacy terminals, jump-host sessions into legacy Unidata
If it has data, we get to it.
Self-building
Agents continuously scan source systems for new objects, properties, and relationships. New data gets absorbed into the ontology and connected to everything related automatically.
- The ontology grows with your institution: no manual modeling required.
Self-healing
When upstream schemas change, agents detect the drift and remap the pipeline.
- No brittle ETL that breaks silently
- The ontology stays accurate without manual maintenance
