The B612 Asteroid Institute has developed the Asteroid Discovery, Analysis, and Mapping (ADAM) platform to analyze and understand asteroid data sets. ADAM uses Google Compute Engine to perform precision cloud-based asteroid orbit propagations, orbit determination, targeted deflections, Monte Carlo impact probability calculations, orbit visualizations, and asteroid discovery. Our vision with ADAM is to create a cloud-based astrodynamics platform available to the scientific community that provides a unified interface to multiple tools and enables large-scale studies. ADAM includes pre-configured settings to match common practices, such as the use of various time standards and coordinate frames, removing the need for users to perform any necessary transformations for comparison to results from external tools. ADAM's architecture consists of a web-service front-end, API interface, cloud-based storage, and cloud-based compute engines encapsulating multiple tools for computation and analysis.

We present the overall architecture and technical implementation of the ADAM platform, including planned and existing services. We go into greater depth about ADAM’s object precovery service, detailing the procedures used to normalize and index observation catalogs, the search algorithm, and the cloud computing infrastructure employed. We also describe the platform’s performance and present results of precovery searches both to extend the arcs of asteroids discovered by the Tracklet-less Heliocentric Orbit Recovery (THOR) algorithm, and to link orbits of the 1.2 million known minor planets with observations in the NOIRLab Source Catalog (DR2).