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Enhanced U.S. Air Force Mission Capability with AI
The RSO has worked extensively with C3 AI to optimize fleet maintenance, increase aircraft availability, and minimize downtime.
The Predictive Analytics and Decision Assistant (PANDA) toolkit, powered by the C3 AI Platform and C3 AI Readiness. Application, identifies aircraft systems and components at risk of failure, provides evidence for the need for proactive maintenance, and ensures availability of the right parts at the right place at the right time for maintenance.
The U.S Air Force has selected PANDA and C3 AI as the Systems of Record for all predictive maintenance. This solution monitors 3,110 aircraft across 16 aircraft platforms and has 8 applications and 750+ active users.
Processed sensitive mission and EW data at the edge for pilots, planners, and analysts
The Crowd Sourced Flight Data (CSFD) Program accelerates mission data collection and processing cycles.
It enables rapid Electronic Warfare (EW) reprogramming, informs operational planning, and provides operational reconnaissance.
CSFD reduces risks to future weapons programs while solving immediate COCOM needs, starting with F-35A.
Provided AI for timely hypersonic trajectory modeling
Modeling hypersonic missile trajectories through physics-based approaches can be time consuming and non-comprehensive.
Through generative models, MDA can provide scientists and analysts a dynamic model capable of generating enough trajectories to accelerate the development of defensive capabilities.
Rapidly analyzed and summarized flight test data
The MDA conducts flight tests that generate hundreds, if not thousands, of data artifacts from a single test. These tests are generated by a variety of sources, come in a variety of different formats, and often become scattered across the enterprise.
C3 Generative AI provides a allows analysts to ask natural language questions to rapidly identify and understand historical flight test results, reducing the time to insights by a matter of weeks.
Gained an enterprise view of initiatives for enhancing fuel efficiency and reducing emissions
Air Force Operational Energy helps mitigate operational risk to the warfighter and optimizes how the Air Force uses fuel by developing and championing energy-informed solutions.
C3 AI developed a scalable AI-enabled predictive analytics application to provide an enterprise view of USAF energy optimization initiatives. The applications also predict fuel consumption for aircraft platforms, starting with the
Generated stochastic options to recover loss of regional strategic capabilities
Warfighting resiliency depends on reallocating supply chain storage and missions when adversaries impact transportation facilities.
C3 AI worked with the office of CDAO to develop an application that fuses logistics and intelligence data and recommends strategic options to recover supply chain losses in the area of operations.
Aggregated and visualized command readiness for USSOCOM enterprises
Special Operations leadership realized that readiness levels must be tracked across manpower, equipment, training, and financials for mission achievement.
C3 AI worked alongside CDAO team to develop precision dashboards that provide real-time command visibility across staff focus areas, mitigate risks, and ensure holistic alignment across the enterprise.
Enabled Joint Staff J4 Logistics Feasibility Planning for complex operational COAs
Rapid and effective planning cycles between joint warfighting functions requires logisticians and planners to quickly measure courses of action.
C3 AI and CDAO team developed a logistics supportability application that ingests supply data, joint doctrine, and operational courses of actions (COAs) to provide a visibility and assessment tool for joint planners forecasting COA feasibility.
Accelerated post-mission analyses of critical systems for launch reliability
Post-mission analyses are critical to ensuring successful future rocket launches. However, identifying anomalies in these systems is difficult and time-consuming.
The C3 AI and Aerospace Corporation team extended C3 AI Readiness to support rocket launch assurance. This application enables program managers and technical analysts to rapidly identify and resolve reliability problems surfaced by sensor-based algorithms (SBAs). It transforms raw sensor data into prioritized predictive alerts to provide contextual understanding while offering robust workflow tools for technicians to act on these problems for rapid resolution.
Improved deployment of staffing models for optimal billet fill rates
USMC model managers and Marine monitors require lengthy lead times to analyze and fill the requirements identified in the Authorized Strength Report (ASR).
The USMC Staffing Goals application accelerates time-to-insight by seamlessly ingesting ASR requirements, effectively identifying available Marines, and rapidly experimenting with different user-defined scenarios.
This application empowers force strength experts to successfully align Marines with the ever-evolving requirements of the USMC.
Created contested logistics control tower application for USTRANSCOM
The Global Operations Center Application enables a common view of upcoming and ongoing TRANSCOM missions, including AI-powered monitoring and alerts for at-risk missions.
The application provides a near-real time view and continuous monitoring of global logistics operations, ensuring resiliency and increased situational awareness.
Allowed rapid strategic scenario experimentations for actionable force readiness insights
Readiness Analytics Visualization Environment (RAVEN) is a transformative national defense strategy tool designed for swift scenario analysis. It assesses the impact on both material and personnel readiness throughout the global force.
RAVEN simplifies various analyses, guiding force providers and operation planners through configurable inputs. Once the model runs, it generates insightful visualizations that help analysts understand the potential effects of different courses of action on force readiness.
RAVEN enables informed decision making by allowing iterative experimentation in minutes, not days; while providing comprehensive analyses to support prepared courses of action.
Coordinated facility and item logistics of Class III and Class IX supplies
The C3 AI Contested Logistics Application for DLA J3 integrates wholesale-to-consumer supply chain data to provide near-real time visibility of Class III (Fuel) and Class IX (Repair Parts) inventory and procurement data.
C3 AI Contested Logistics organizes disparate data systems from military services and supporting agencies to enable AI-powered risk prediction and supply chain resiliency.
Used AI to evaluate the trustworthiness of Position, Navigation, and Timing data
The US Space Force faces challenges providing assured position, navigation, and timing (PNT) data to civilians and warfighters because of variable data quality and adversarial EW and IW attacks against sensors and databases.
C3 AI's multi-domain data fusion and data veracity solutions give the warfighter insight into the trustworthiness of PNT data – including identification of adversarial attacks against sensors and datasets – using AI, ML, and physics-based approaches displayed in a common operating picture and a data marketplace.
Used AI to model and forecast storm surges and plan engineering response
For coastal communities, predicting storm surges and reinforcing the flooded areas can save homes and lives.
C3 AI worked with the US Army Corp of Engineers to develop an application to integrate CSTORM-MS and other data to forecast storm surges, helping with emergency planning, disaster response, and protective infrastructure engineering.
Used AI/ML to assess risk and flag anomalies from federal security clearance applicants
Screening and adjudicating security clearances can be a manual and time intensive process. Data analysis, investigations, and recommendations using individual systems are inefficient.
C3 AI worked with the Defense Counterintelligence and Security Agency to help accelerate the assessment and adjudication of security clearance applications using AI/ML techniques.
Generated high-fidelity, multi-dimensional, explainable objects for downstream analysts, planners, and application developers
Multi-Modal Entity Fusion (MMEF) resolves, synthesizes, and fuses geo-temporal data from multiple domains to create a trustworthy foundation of objects that enables battlefield decisions at the speed of relevance.
C3 AI Decision Advantage's foundational module, MMEF, is an API-accessible, open, multi-domain, multi-modal data fusion engine and object repository that enables application development, intelligence analysis, and accelerated kill chains.
Delivered a model marketplace and orchestration tool for soldiers
The U.S. Army is developing a next generation expeditionary, maneuverable intelligence ground station to support Multi-Domain Operations and Long-Range Precision Fires during large-scale combat operations. The solution requires the deployment of hundreds of machine learning models at the tactical edge.
C3 AI provides intuitive machine learning model management capabilities to soldiers on the battlefield as part of a classified suite of tools that deploy at the edge and reduce the time from sensor to shooter, enabling rapid course of action development and execution in response.