Modeling the interior structure of terrestrial planets has become one of the most computationally-intensive, big-data problems in the physical sciences with demonstrated utility in assessing hazard, locating explosions and characterizing plate tectonics. Multi-disciplinary advancements have led to a proliferation of dynamical simulations and model snapshots from seismic tomography. Reconciling seismic models and data with simulations from geodynamics, mineral physics and geochemistry is crucial for robust thermo-chemical interpretations. Such cross-disciplinary initiatives have been impeded by discrepant spatial scales, observational or theoretical assumptions, and lack of data validation algorithms. We present methods and data formats that will facilitate rapid prototyping of multi-scale models by reconciling and assimilating features ranging from reservoir (~0.1 - 10 km) to global scales (~500 - 5000 km). Our approach involves three complementary aspects: (1) Code repositories comprising modular libraries with model classes and scalable HDF5 formats for archival, (2) API (Application Programming Interface) calls for querying model and data evaluations with fast, benchmarked forward solvers, (3) Web-based applets for visualization and outlier analyses. Both (1) and (2) are utilized by (3) and can be accessed on the client side with Jupyter notebooks and command-line tools. This proposal to the Computational Infrastructure for Geodynamics (CIG) will provide an opportunity to document AVNI and finalize its release according to CIG standards. AVNI tools will help with identifying regions of scientific interest, validating new techniques, planning future instrumentation deployments, and testing hypotheses about the Earth's deep interior. An additional educational component, not funded through this subaward, will provide training of undergraduates in the analysis and visualization of planetary models, preparing them for a research career in the geosciences.