Blattner Technologies delivers a simulation platform for enterprise AI and ML development on PC. Teams across industries prepare, analyze, and manage machine learning data and models through a Unity-based desktop app. Low to no-code tools with graphical interfaces streamline predictive analytics, while federated learning keeps data secure at its sources.
Users train models on large datasets with autoscaling distributed processing and integrated explainability for debugging and trust-building. Jupyter Notebooks unify experiment and production code, alongside support for libraries like TensorFlow and PyTorch. Granular security controls ensure regulatory compliance. This utilities-focused software suits data science professionals seeking privacy-preserving ML workflows.
Blattner Technologies empowers companies in a range of industries to easily build production-ready AI solutions for maximum data science productivity.
About this software:
Blattner Technologies offers an Enterprise AI/ML development platform that allows organizations in a range of industries to put their data to work — no matter where it resides, with the only commercially available Federated Machine Learning platform on the market today. Collect data at the edge, uncover insights in your data, analyze ML model training, and make better decisions with predictive analytics.
Product Features:
· Unity-based desktop application facilitates the preparation, analysis, and management of all ML data and models.
· Low to no-code ML development simplifies predictive analytics with graphical point-and-click capabilities.
· Federated ML development enables secure privacy-preserving ML training by deploying training to data sources, relaxing the need to collect data at a central point.
· Autoscaling distributed ML training enables easy development for large-scale datasets.
· Seamlessly integrated ML explainability helps in model debugging, revealing model risk, and increasing trust with application stakeholders.
· Integrated Jupiter Notebooks enable the development and management experiment and production code in one place.
· Granular level security controls (including data cell-level security) help support compliance with industry regulatory standards.
· Support for leading open-source ML Libraries (e.g., TensorFlow, PyTorch) enables users to choose “the right tool for the right job.”
For more information contact us at https://blattnertech.com
