We are redefining networks and intelligence with our pioneering work in ontology-driven AI systems,
built on the foundation of the Basic Formal Ontology (BFO).
Our research and applications aim to transform industries by enabling seamless interoperability
and empowering informed decision-making across organizations.
Our research applications have been developed in close collaboration with the University at Buffalo, home to the creators of the Basic Formal Ontology. This partnership enables us to bring cutting-edge ontology research into practical, scalable applications for diverse industries, from healthcare to finance.
By combining our expertise in ontologies with the vision of BFO’s creators, we bridge the gap between academic research and real-world implementation.
We extend the power of the Basic Formal Ontology (BFO) and ontologies by incorporating advanced tools like Directed Acyclic Graphs (DAGs) and Bayesian Networks, which are specialized forms of DAGs used for probabilistic reasoning. While DAGs model dependencies and relationships in a clear, acyclic structure, Bayesian Networks go a step further by assigning probabilities to these relationships, enabling powerful predictive and inferential capabilities.
By embedding these tools into our systems, we enable organizations to:
- Model Dependencies: Use DAGs to map workflows, relationships, and data flows with clarity.
- Predict and Infer: Leverage Bayesian Networks to perform probabilistic reasoning and uncover likely outcomes in uncertain environments.
- Make Data-Driven Decisions: Utilize causal reasoning to guide complex decision-making with confidence.
By bridging ontologies, data engineering and data science principles with advanced AI frameworks, we unlock groundbreaking possibilities in research. These interconnected systems are designed to structure knowledge, predict outcomes, and drive actions, creating an unparalleled foundation for AI-driven solutions.
We are connecting Knowledge and AI to transform how we research and innovate