Decision Making in Action
Biometrics
Because troops deployed around the globe require fast and reliable identity confirmations, we have developed the best possible solution that can evolve with technological advances to meet their needs.
Disaster Relief
The scale and impact of natural disasters can present a significant challenge to governments, emergency responders, and volunteers. AI enables near real-time insights including location of disaster victims, areas of impact, safest evacuation routes, and the development of weather systems.
Hive/SDH
DMC is using machine learning and artificial intelligence along with evaluation and test range software technologies to accelerate development of Electronics Resurgence Initiative (ERI) hardware-focused efforts. This work includes transition of ERI technologies onto classified datasets.
IoT Sensor Calibration
We developed a new method for automatically calibrating Internet Of Things sensors. This method can produce large monetary savings for companies that maintain large, deployed arrays of sensitive IoT sensors by negating the need for service personnel to calibrate or replace them over time.
Media Forensics: Deepfakes
Initiatives like the MediFor Project have been established to reverse the power of machine learning to stop the spread of disinformation through the creation of widely accessible tools that distinguish between authentic and doctored media.
Quantitative Crisis Response (QCR)
QCR was designed to speed awareness and aid in early decision making during times of crisis. This cross-agency platform was first deployed during the Ebola crisis and is still actively supporting military information operations.
Predictive Maintenance
Imagine having the ability to respond to a maintenance concern before an emergency ever occurred. With predictive maintenance, data is collected to monitor equipment and find patterns that can predict and prevent failures.
"Vanity Free" Computing
We are the first company on the East Coast to deploy Open Compute Project (OCP) hardware in support of government use cases. By adopting optimized, vanity-free computing, clients are able to attain better cost efficiency and higher performance.
Data-Driven Discovery of Models
The Data-Driven Discovery of Models (D3M) program aims to develop automated model discovery systems that enable users with subject matter expertise but no data science background to create empirical models of real, complex processes.
DARPA PROTEUS
The Defense Advanced Research Project Agency’s (DARPA) Prototype Resilient Operations Testbed for Expeditionary Urban Operations (PROTEUS) program will enable assessment and exploration of new approaches to combined arms operations involving coordination of effects in multiple domains.
Container Safe Software
Container safe software determines if an untrusted analytic container is adversarial or benign. It allows for cross-system and cross-organization analytic sharing with the assurance that risk mitigation methods exist. Sharing of packaged software analytics from untrusted sources will not attempt privilege escalation, data corruption, data exfiltration, scanning, or breakout activities.
Cloud Federation
To attain maximum compute and cost efficiencies, we maintain a core competency in federating and moving workloads between compute clouds and compute centers. We work extensively with academic compute centers, commercial clouds, DoD high performance computing, and on-premise clouds.