AURA’s AI work centers around predictive analytics, deep learning, and data-augmented decision making. Training on large historical data sets allow AURA’s AI algorithms to support long-term strategic decisions, urgent tactical response, while also offering clients the best possible user experience.
Innovative AI algorithms being built by AURA will allow crucial decisions to be guided by data. AURA’s focus on AI is geared towards increasing the speed and efficiency of human-in-the-loop intelligence, not replacing human intelligence. Below are details about a few selected AURA AI products:
US Air Force aerial ports are responsible for moving nearly 300,000 tons of cargo per year. However, redundant manual processes and other inefficiencies create procedural waste which can be prevented through the application of AI. To solve these issues, AURA is developing Atticus™, a sustainable, end-to-end AI product with three major goals:
- pallet preparation recommendation
- readiness assessment
- cargo tracking
Given the uncertainty in the world today, aerial ports must be ready to ramp up operations quickly in the event of a conflict, and Atticus™ will play a key role in increasing readiness.
- OrbitOutlookOptimizer™ (O3)
As the number of satellites in orbit increase due to the commercialization of space technology, tracking of space debris must ensure that avoidable collisions do not occur. Non-traditional data sources, such as sensor observations from academia or industry, have not yet been properly utilized due to the difficulty of integrating them within traditional astrophysical calculations.
AURA is developing deep learning algorithms to not only unify disparate data types but also grade the uncertainty and usefulness of the non-traditional information.
Diminishing Manufacturing Source and Material Shortage (DMSMS) issues result when there is a loss (or impending loss) of component manufacturers or raw-materials suppliers, often in the context of electronic components. Many factors affect part obsolescence, but the majority of DMSMS concerns arise from technological improvements, decreased demand, and material shortages. Saker™ is a decision-augmentation system that greatly increases efficiency in the part replacement cycle by providing more structured and relevant information than is traditionally available, while scaling to meet user demand.