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The Kepler mission observed approximately 200,000 stars for four years and identified over 34,000 transit-like events. The Kepler Robovetter translates the logic used to discriminate between "likely planet candidates" and "false positives" and automates the evaluation of large Kepler data sets which are available at the public archive. The expected audience is active astronomers in the scientific community. NASA acknowledges the SETI Institutes primary role in authoring and producing the Kepler Robovetter under Cooperative Agreement Number NNX13AD01A.

The Kepler Plotting Program was developed as an aid to understanding the publicly available data files that have been released by the Kepler project. This tool allows end users to reproduce plots used in project documentation, facilitates the user's scientific understanding and promotes the utilization of the Kepler science data products . NASA acknowledges the SETI Institutes primary role in authoring and producing the Plotting Program for Kepler Planet Detection Efficiency Products under Cooperative Agreement Number NNX13AD01A

Kepler K2 Cadence Events (K2CE) is a data visualization / manipulation Python application which runs on publicly available data from the NASA Kepler, K2, and TESS missions to produce annotated light curve plots and, optionally, filtered versions of the input data files.

KeplerPORTS (Kepler Planet Occurrence Rate Tools ) is a software tool that illustrates the use of Kepler's planet occurrence rate data products by generating contour plots for s elected s ample files . NASA acknowledges the SETI Institutes primary role in authoring and producing the KeplerPORTs (Kepler Planet Occurrence Rate Tools) under Cooperative Agreement Number NNX13AD01A.

The Data Processing Pipeline is a central element of the Kepler Ground Data System. The Science Processing Pipeline is used to analyze stellar photometric data from the Kepler spacecraft and report results to search for planets within the Kepler photometric dataset. The software data release is to allow the scientific community access to the details of the software algorithms within the Science Processing Pipeline. The pipeline performs pixel-level calibration, photometric analysis, systematic error correction, transiting planet detection, modeling and diagnostic testing of potential transit signatures, attitude determination, stellar target management, and monitoring of instrument health and performance.