Behind every great knowledge graph or artificial intelligence (AI) assistant is a robust taxonomy or ontology.
Structure information to fuel machine-driven solutions
Graph- and AI-based solutions can sometimes look like they were created by magic. But they’re actually the results of careful and rigorous information design. Machines can’t understand content or business context without additional, explicit schemas to guide them. These types of applications generally rely on a well-structured set of information to match content to the user’s intent, and provide relevant, meaningful answers.
Before embarking on a project to build a knowledge graph or machine learning solution, content must be adequately defined, structured, and described with taxonomy and/or ontology. Ontologies help provide the necessary context and logic to help machines understand and apply patterns.
Define the right schemas and structures to support main use cases
Whether you’re implementing your first customer service chatbot or developing a graph-powered search, we can help you deliver the information your users need. We work with you to help define the right schemas, taxonomies and ontological structures to support graph or AI use cases.
How can we help you get more out of your information?
Let’s talk about how we can help you make your content more intelligent.