Your institution's knowledge, structured for AI.
Ontography Labs builds the ontology of your institution, turning fragmented catalogs, calendars, and policies into a governed knowledge graph. Then every answer is grounded, cited, and yours to control.
Proven in production with the NYU Stern School of Business.
query →
Records × Attributes"Surface every record that matches these constraints."
12 validated matches · cited · 1.4s
Smart models still get your institution wrong.
Not because the models are weak, but because your knowledge was never structured for them. Generic chatbots flatten catalogs, calendars, and policies into a wall of text and hope for the best. We take the opposite approach.
We don't prompt harder. We build the ontology of your institution.
How we make AI trustworthy for institutions.
Structure
We ingest unstructured catalogs, calendars, faculty directories, and policy docs and preprocess them into a knowledge graph with validated entity relationships, so the model never confuses the wrong professor, term, or policy.
Ground
Specialized retrieval agents route every question to the right part of the graph and answer only from approved data, with citations attached. No paraphrasing stale web pages, no invented facts.
Govern
Role-based access, topic-level permissions, approval workflows, and full audit logs put the institution in control of exactly what gets said, with feedback loops that compound accuracy over time.
One knowledge layer. Every product builds on it.
Ontography is the engine beneath our products. The same governed knowledge graph and multi-agent retrieval that powers Campus Intelligence can ground answers for any institution drowning in unstructured knowledge.
Knowledge graph core
Validated entities and relationships replace flat document soup, so retrieval is precise instead of probabilistic.
Multi-agent retrieval
Purpose-built agents resolve compound questions by intersecting results across the graph: courses × instructors × time, in one query.
Grounded & cited
Every response is traceable to an approved source. Answers degrade gracefully, never confidently wrong.
Governed by design
Permissions, approval, audit, and feedback are first-class, not bolted on after the fact.
What we've built on it so far.
Ontography Labs ships focused products on top of the platform. The first is live in production.
Campus Intelligence
“Sternie”An AI assistant that answers student and staff questions across courses, events, and policies, grounded in your institution's approved data. Deployed and proven with NYU Stern.
92%
resolved without web fallback
<3s
average response
More verticals
The same governed knowledge layer applies anywhere institutional knowledge is fragmented and accuracy is non-negotiable. Talk to us about your domain.
Start a conversationWe believe AI should deepen the human side of institutions.
Ontography Labs started with a simple observation: the smartest models in the world still get your institution wrong, because your knowledge was never structured for them. Generic chatbots flatten everything into text and hope for the best.
We build the ontology of your institution, preprocessing unstructured catalogs, calendars, and policies into knowledge graphs with validated relationships, then routing every question through specialized retrieval agents grounded in approved data.
Campus Intelligence, our first product, proved it with NYU Stern: when students could ask in plain language and trust the answer, course planning and campus navigation became something they actually enjoyed. For administrators, the same shift meant 40-60% of routine questions handled automatically, fewer repetitive tickets during lottery season, and staff freed for the cases that actually need a human. We're bringing that rigor to every institution.
Give your institution answers it can trust.
To book a demo or get in touch, email us at hello@ontography.ai.
hello@ontography.ai