Abstract: A method for providing expected results predictions includes receiving a test case that uses data records from one or more applications and predicting, using an artificial intelligence engine that uses a machine learning model configured to predict test case outcomes, a test case outcome for each test cycle of the test case, the machine learning model being trained using classified actual outcomes of test cases having similar test case requirements as the test case. The method also includes comparing, using a test automation framework, the predicted test case outcome for each test cycle of the test case to an actual outcome for each test cycle and generating a report indicating a result of the comparison of the predicted test case outcome for each test cycle of the test case to the actual outcome for each test cycle.

Abstract: A method for automatically identifying test case data includes receiving a plurality of data records from one or more data producer applications and classifying data records of the plurality of data records into test data clustering model. The method also includes receiving input indicating one or more test case requirements and generating, based at least on the one or more test case requirements and the test data clustering models, at least one test case blueprint indicating at least one test data clustering model that corresponds to the one or more test case requirements. The method also includes, in response to instructions to perform a data test corresponding to the test case requirements, using the at least one test case blueprint to populate test case data using data records corresponding to the at least one test data clustering model indicated by the at least one test case blueprint.