Since 2004, Mosaic has been helping aerospace and air transportation companies deploy the most advanced custom data science at scale. We have designed and developed aviation machine learning solutions and decision support tools for NASA, the FAA, DoD, and more. As a leading provider of advanced aviation solutions for a diverse set of federal and commercial aviation customers, many of Mosaic’s projects have demonstrated millions of dollars in annual cost reductions. Our dedication to achieving customer objectives through innovative techniques and our creative approach to complex air transportation challenges sets us apart – delivering impartial, data-driven results with an eye toward sustainability.
Mosaic developed Explainable AI in Lunar Operations to support lunar rovers using imagery data from hardware to assist NASA rovers in assessing the traversability of a given region of terrain, supporting increasingly autonomous operations.
This blog discusses the decision process for adjusting flight schedules in response to weather events using advanced analytics.
Mosaic applied our robust data analytics expertise across disciplines to develop novel, data-driven models that identify anomalous behavior for a leading aerospace government agency.
Mosaic helped a commercial airline integrate custom machine learning to predict departure runway and taxi-out time, cut operational costs, and improve the customer experience, aiding in reducing fuel emissions with AI.
Mosaic brought its deep expertise in aviation to design and test effective machine learning models that would predict the arrival and departure assignments of flights, helping facilitate automated testing and deployment of advanced predictive decision-support tools.
Aerial Vantage has received Federal Aviation Administration (FAA) approval of a waiver allowing it to conduct advanced remote sensing missions using unmanned aircraft systems (UAS, or drones) over a large ranch in Florida.
In our white paper, Mosaic examines fresh machine learning based approaches to more accurately forecast airline seat demand.
Optimizing how airplanes take off is a perfect use case for fusing IoT and predictive analytics.
We examine how to apply ML & AI for the IoT use case of mining for aircraft performance insights.
Being able to accept machine learning outputs in the decision making process is critically important, especially in Air Traffic decisions.