Machine Learning for Everyone: Democratizing AI
Advanced solution for any business, where you can create zero-coding models and centrally manage them, controlling all stages of the life cycle so the models are always up-to-date and growth-hacking.
Explore data before building models: identify patterns and anomalies, test hypotheses, and select variables with visualization tools, profiling, correlation matrices and cluster analysis.
Visual designer for building models, including nodes for processing datasets, choosing algorithms, interpreting their work and assessing quality. Comparing the models will help you choose the best ones for future use.
Models in Polymatica ML are created from ready-made elements, so the user can quickly test various hypotheses, compare the resulting models and quickly select and implement a champion model. Thanks to this approach, the transfer of models to industrial operation occurs in a matter of minutes instead of months. The platform helps business, analysts and IT department cooperate effectively to get a better result.
The Polymatica ML repository is designed become a centralized repository of both machine learning and physics and mathematics models thanks to the ability to import them from various environments, primarily Python. The repository can host models built on both structured and unstructured data. Providing all the necessary functionality to apply the ModelOps approach, the common repository allows you to organize transparent work with models in such a way that they bring maximum business value.
Polymatica ML is part of the Polymatica Platform and can be combined with Polymatica Analytics and Polymatica Dashboards modules, or separately, depending on the tasks to be solved.
Polymatica Analytics is a tool to explore data in pivot tables, including big data in near real time. Polymatica Dashboards helps to visualize metrics to monitor business processes and results for data-driven solutions.
We propose to launch a proof of concept (POC) project to confirm the effectiveness of using a unified full-cycle machine learning platform and to obtain additional business benefits through the use of modern AI technologies.