
A Proven Leader in Data Science & Engineering
Our mission is to help customers optimize their data and transform it into smart, critical information for rapid consequential decision making.
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Established in 2015, NNData focuses on solving complex data integration challenges across multi-variate data sources using our AI-Enabled ETL commercial software product NNCompass, white-glove Data Engineering approach, and Applied AI / Data Science Professional Services. Leveraging proven enterprise data management processes, best in breed technology, and forward-leaning data science-based approaches for converting unstructured data in to structured normalized intelligence. We know how to tackle and solve unique data solutions, package, and deliver them for the US Public Sector, International Agencies, and for Fortune 500 companies.

Data Engineering & Optimization
Data Administration, Profiling, and Management
Get a unified view of data across your organization. NNData will aid in deriving new intelligence through aggregation, integration, structure, automation, and operationalizing data from disparate and complex sources. Our practices bring current and historical data into a single unified format so that advanced applications and improved business process can be adopted quickly and accurately.
Applied AI / Data Science
Machine Learning, Knowledge Graphs, and Data Processing
NNData applies state-of-the-art Machine Learning (ML) techniques to increase the confidence of mission stakeholders in understanding their decision-space and Situational Awareness (SA). We augment open-source Natural Language Processing (NLP) and deep learning-based ML tools (e.g., neural networks and Q-learning) with emerging research techniques to obtain industry leading accuracy for topic and entity extraction, entity-to-entity relationship discovery and correlation, pattern detection and optimization, anomaly detection, and task optimization. These tools and techniques incorporate and integrate with cloud-enabled microservices and ML Ops platforms to support data ETL, content deduplication, pattern-of-life analyses, discovery of irregular or abusive incidents of patterns of behavior, among other use cases.


AI-Enabled ETL and Digital Process Automation