Abstract: Systems, methods and apparatus are provided for an end to end control automation workflow using a distributed network. The data segregation layer may assimilate data from a variety of enterprise sources. A trust engine may validate the data from enterprise sources against enterprise security standards. The system may use a distributed network to validate the data from the various sources and populate a distributed hash table. The distributed network may be a Holochain® framework. The system may include an automation layer that uses robotic processing automation scripts to validate data against a system of record and flag exceptions. The automation layer may provide data to a user interface layer. The user interface may include an interactive dashboard for presenting a range of detailed reports.

Abstract: Systems, methods and apparatus are provided for an end to end control automation workflow using a distributed network. The data segregation layer may assimilate data from a variety of enterprise sources. A trust engine may validate the data from enterprise sources against enterprise security standards. The system may use a distributed network to validate the data from the various sources and populate a distributed hash table. The distributed network may be a Holochain® framework. The system may include an automation layer that uses robotic processing automation scripts to validate data against a system of record and flag exceptions. The automation layer may provide data to a user interface layer. The user interface may include an interactive dashboard for presenting a range of detailed reports.

Abstract: A guided sampling tool guides the sampling of datapoints in large datasets. Generally, the guided sampling tool applies a machine learning algorithm to a database of historical issues encountered by an organization to guide the sampling of a large dataset. The guided sampling tool can evaluate and change provided variables and weights for performing a sampling. After the datapoints are sampled, the guided sampling tool compares the historic transactions represented by those datapoints to baseline images to determine if the historic transactions encountered a problem or issue, which would affect the overall quality assessment.

Abstract: A guided sampling tool guides the sampling of datapoints in large datasets. Generally, the guided sampling tool applies a machine learning algorithm to a database of historical issues encountered by an organization to guide the sampling of a large dataset. The guided sampling tool can evaluate and change provided variables and weights for performing a sampling. After the datapoints are sampled, the guided sampling tool compares the historic transactions represented by those datapoints to baseline images to determine if the historic transactions encountered a problem or issue, which would affect the overall quality assessment.