Seclea Prepare accelerates the necessary checks that data scientists and engineers have to make before using a data set. Ensuring that machine learning models will be build on high quality data sets.
Seclea Platform can easily to be integrated with any data source. With a few steps, data can be ingested from popular data stores including local machines and infrastructures. Seclea’s pre-built connectors make it an easy and simple process.
Seclea Platform assesses the data sets to detect the presence of Personal Identifiable Information (PII). Data scientists, engineers and the project manager can then decide what action to take regarding the PII in the data set in compliance with the regulations and the project’s requirements.
Seclea marks the locations in the data sets to for quick reference, accelerating remedial action to speed up getting on with machine learning model development.
Seclea Platform enables data scientists, engineers and project managers to monitor all data set transformations. Enabling them to track data set evolution and assess the value of data transformations on machine learning model development and potential compliance requirements.
Monitoring the impact of data transformations enables organisations to ensure that they abide by the Responsible AI governance framework – tracking and documenting any and all actions taken to design, develop and deploy an AI application.
Seclea Platform automatically assesses your data sets for potential imbalanced data and bias. Seclea provides data scientists and engineers tools to fix data imbalance and mitigate bias in data sets.
Seclea generates the necessary reports for project managers, internal and external stakeholders to gain confidence that data scientists and engineers have taken due care when handling data sets for fairness and transparency.
Seclea Platform monitors and tracks all actions taken by data scientists, engineers and project managers when preparing data sets for machine learning and deep learning model development. Seclea analyses these actions for compliance with Explainable AI and Responsible AI frameworks along with application specific and AI regulatory requirements.
The analysis report enables data scientists, engineers and project managers to ensure that they meet the necessary requirements every step of the way and can report with evidence. Gaining the confidence of both internal and external compliance auditors.
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