PlatformOur AI Approach
Artificial intelligence built for higher education
Through a combination of technology, people and innovation, our AI empowers colleges and universities to solve student service and support challenges both today and into the future.
Dr. Lloyd Holmes, VP of Student Services
Big higher education data
How our AI Platform works
Ocelot takes a big data approach to building our platform which is backed by our own proprietary software and best in class technology in the AI market.
Our is based on over four million student interactions, and hundred thousand questions across our entire network of schools. Individual schools do not need to build their own dataset or supervise their own AI. Instead, the AI for each school is learning and training from all student interactions across the entire Ocelot network. Our datasets are much larger than what a single school can offer.
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.
Quality in, quality out
The golden rule of data science is quality inputs, which improve the likelihood of quality of outputs. Ocelot’s AI is built on this principle and is fuel for impactful student engagement.
By using a combination of sources of information, our AI Platform can provide holistic answers to users while also helping guide them towards other questions they may not have known to ask.
How we ensure our AI is improving responsibly
Always getting smarter
All AI-powered platforms require some level of human supervised machine learning. Our team consists of data scientists, content creators, and conversation design experts with a combined 70 years of higher education experience that verify and classify our data. This ensures all content stays up-to-date with the latest regulations and trends.
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.
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