Modus Operandi
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Method

AI/ML & Ontology

Movia® applies semantically anchored machine learning - artificial intelligence governed by your organization's own ontology

Surround your data with meaningful linked relationships and attributes, wrapping knowledge with deeper intelligence, resulting in actionable insights in a trusted source.

Is semantically anchored machine learning for you?
  • Do you have too much data and not enough actionable information?
  • Is your research limited because your intelligence is arranged in stovepipes instead of objects of interest?
  • Do different parts of your organization use different words for the same thing, making it difficult to mediate and harmonize your structured and unstructured data stores?
  • Would it be beneficial for your analysts to search in a vocabulary native to their own domain?

Movia® Builds on Your Organization's Ontology

  • Your team's data is rich with information, not just keywords
  • Movia® uses AI/ML to look within your data for information objects and relationships, and then builds extensive metadata that establishes linkages and correlations between these objects, based on your organization's ontology
  • A dynamically applied ontology, your semantic model, defines the explicit relationships between your knowledge objects. This process gives the content and its context a machine-understandable meaning, and enables the entire system to view information not as a flat file, but as an interconnected knowledge graph

Movia® Gives Your AI/ML More Context to Work With

  • Unstructured file formats lack the granular data and metadata required by modern artificial intelligence and machine learning tools
  • Movia® breaks the document "blob" into information elements with context, turning paragraphs into knowledge objects and applying metadata to include structural elements and provenance — who, when and where it has been used. This provides context to the information, allowing for smarter query, but also provides significantly more context to AI/ML algorithms for better automation results
  • In essence, your content writes itself to address the information needs of the user
R&D

Our Research Capabilities

Our research capabilities cover the spectrum of the key technologies for orchestrating the power of human and machine analysis to drive smarter decisions. We have coalesced our R&D activities to focus on enabling the realization of living intelligence — the partnering of humans and machines to share, collaborate on, and analyze data in support of mission-critical decision making.

Semantic Modeling and Integration

Ontologies. Model creation. Model alignment and mapping. Inference-driven on-demand query. Domain and subject-matter-expert knowledge elicitation.

Artificial Intelligence and Machine Learning

Semantic reasoning and logical approaches for automated reasoning. Rule generation. Auto-classification techniques. Partial-pattern recognition. Supervised and unsupervised machine learning algorithms.

Information Fusion

High-speed multi-source data ingest, cleansing, enrichment, and correlation. Metadata tagging. Data alignment and integration. Large-scale and cloud-scale graph generation. Auto-extraction and auto-classification. Common referencing of observational sources.

User Interface Design and Usability

Usability assessment. Highly linked knowledge search and discovery. Semantic wiki. Graph-based search and visualizations. Map clients and servers. Small form factor devices.

Human-Machine Orchestration and Analytics

Object-Based Production (OBP). Adaptive case management. Intelligent, contextually aware data analytics. Descriptive, predictive, and prescriptive analytics. Pattern-of-life analysis. Graph heuristics for matching, association and reasoning. Social Network Analysis (SNA). Temporal analysis. Content similarity analysis.

Text Analytics

Text analysis and tagging. Automated co-referencing. Part-of-speech tagging. Lexical construction.

Movia® Mediates Between Your Data Stores

  • Largely stove-piped data components leave your users without a common operating picture
  • On the Army's Guardrail Common Sensor program, data was exposed via a semantic model, or ontology, which is capable of mediating and harmonizing heterogeneous structured and unstructured data stores
  • On DCGS-SIGINT, an entity extractor semantically tags concepts by applying the ontology of the Joint Command, Control and Consultation Information Exchange Data Model, allowing analysts to search in a vocabulary native to their domain

Movia® Raises the Data-to-Noise Ratio

  • Data lakes become contaminated when everything is ingested and nothing is assessed
  • Movia® leverages AI/ML and LLMs with filtering, phrase extraction and summarization services prior to data ingest, reducing data lake contamination
  • Movia® is an ontologically governed, AI/ML/DL/LLM enabled, open architecture Object Management System
This research used to take weeks. Now it takes minutes.
- Satisfied DoD Customer
You just reduced our research time by 90%
- Satisfied DoD Customer
This revolutionizes our entire operation.
- Satisfied DoD Customer
Customer benefit:

Higher quality, faster decisions are made based on the best information available and supported by machine and human analysis.

Explore

Our technology explained

Core Technology

Movia® Engine

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Data Model

Knowledge Graph

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