Enterprises have an ever increasing wave of data they can use to their advantage. One approach is to use brute force through more and more in-house servers and cloud resources. This entails pouring everything (data, documents, images, videos, files, databases) into a data lake and going at it with a variety of analytics — hoping to discover something that will change your business. This a shot in the dark at best.

The MO approach is more tactical. MOre immediate.


In Movia each piece of data is a fact. Facts use semantic models to know how to display themselves. Each fact also has a pedigree, source, provenance, and a degree of reliability.

Clusters of facts create an entity, such as “John” or “Beth” and so on.

Similar entities create a category, such as “Employees.”


Relationships between facts are also facts.


The Movia REASONER is used to fill-in-the-blanks in the data, match, merge, infer, and auto-classify.


Movia Agents

Attach a Movia AGENT to your data lake or to the fire hose of data streaming into your organization. Then use logical, semantic models that represent your business objectives, and empower reasoning engines to monitor for the critical patterns that are important to you, right now. When you detect a pattern, make a real-time decision. Reach out and “tap, tap, tap…” the organization on the shoulder. Visually explain what is headed your way.

Real-time analysis – predict a threat or opportunity – alert your people and react. NOW!

Movia - Analyze, Predict, Warn

Our Movia PLATFORM provides:

  • Semantic graphs (predicate and triple-stores)
  • Layered, distributed ontology models
  • First-order predicate logic for real-time reasoning
  • Inexact stochastic graph matching algorithms
  • Entity management
  • Threat and opportunity detection algorithms
  • Trust and provenance models
  • Context engines that understand space and time
  • User interfaces where the data itself knows how to best visualize itself

Movia Layered Ontology Model

Movia provides a layered ontology model that insulates decision logic from low-level data-source churn