Artificial intelligence with real impact
Learn how Ocelot’s proprietary natural language processing and machine learning AI workflow, comprised of a unique combination of people, process and technology, creates a personalized, 24/7 student support experience.
Dr. Lloyd Holmes, VP of Student Services
Why Ocelot's AI approach is superior
More inputs means better responses so students are more successful.
Immediate "Day 1" value.
New deployments are already primed for launch.
Staff maximizes impact.
The team can focus on the cases that need 1:1 attention.
Quality in. Quality out.
Bigger data. Better answers.
The first driver of AI quality is the breadth of inputs from which the AI feeds on to create responses to student interactions. Ocelot takes a big data approach so students get the best answers.
This centralized architecture means the AI is learning from data across Ocelot’s entire network. Clients benefit from the collective strength of the network that includes millions of student interactions and hundreds of thousands of questions instead of only having a single-school environment to fuel the engagement experience with our platform.
Ocelot also curates comprehensive content libraries to supplement other key inputs (web crawling, internal FAQs, data from integrated platforms) ensuring students get the best answers that a individual school cannot provide on its own.
Human supervised learning
Ocelot’s AI Conversation Design Team takes a unique approach to make Ocelot’s platform smarter. This team consists of data scientists, content creators, and conversation design experts. Additionally, Ocelot has a Compliance and Content Review Committee that has a combined 70 years of higher education experience that ensures that general content stays up-to-date with the latest regulations and higher education trends. In simple terms – Ocelot does the heavy lifting when it comes to managing the technology and building the AI algorithms, so clients can focus on facilitating more impactful interactions with their students.
Dedicated team to expand libraries.
Improving our AI responsibly
Always getting smarter
We use natural language processing (the process of organizing language into structured data), natural language understanding (teaching machines reading comprehension), and deep learning and neural networks (understanding relationships in data) to inform our AI.
This approach, combined with continuous optimization of our knowledge base, regular analysis of intent, entity and dialog data, plus client input ensures a best-in-class experience with our AI.