Wisely deploys ParallelM’s MCenter to ease deployment, operationalize machine learning

ParallelM announced this week that Wisely, a provider of AI-powered fundraising solutions for not-for-profits, has selected ParallelM’s MCenter to operationalize its machine learning. With MCenter, Wisely can deploy and optimize new machine learning applications without needing additional resources to scale its fundraising productivity tool, which uses machine learning algorithms to produce real-time insights that are essential to successful not-for-profit fundraising.

MCenter delivers a unique approach to MLOps, addressing ML production issues head-on by automating ML-optimized continuous deployment and integration, ensuring the quality and performance of live ML applications, and empowering data science and operations teams with innovative visualizations to manage ML applications over time.

MLOps (a compound of “machine learning” and “operationalization”) is the practice of operationalizing and managing the lifecycle of ML in production. MLOps establishes a culture and environment where ML technologies can generate business benefits by optimizing the ML lifecycle to automate and scale ML initiatives and optimized business return of ML in production.

MLOps enables collaboration across diverse users (such as data scientists, data engineers, business analysts and ITOps) on ML operations and enables a data-driven continuous optimization of ML operations’ impact or ROI (Return on Investment) to business applications.

Using MCenter, business teams can mitigate risk, ensure compliance, assess and optimize the ROI of their AI initiatives. By providing a single, unified software solution for the entire ML production lifecycle, MCenter enables companies to move into the critical phase of realizing and scaling ML business value.

ParallelM’s MCenter solution is built to power the deployment, optimization and governance of machine learning pipelines in production so that companies can scale machine learning across their business applications. ParallelM’s approach is that of a single, unified MLOps solution that embeds best practice processes in technology, enabling all ML stakeholders to unlock the business value of AI.

“The integration of ParallelM’s MLOps solution into our platform allows us to provide better machine learning-based predictions, ensure pipeline health and increase the productivity of our customers’ fundraising efforts,” said Artiom Komarov, CEO and co-founder of Wisely. “Data garnered from machine learning and artificial intelligence can truly have a positive impact on not-for-profit fundraising, but the challenge has been scaling up the number of models inside of our application. ParallelM’s MCenter helps us not only deploy more machine learning into production but also manage and optimize its performance in real-world use cases.”

“We’re excited to work with Wisely to help them provide their not-for-profit customers with the most accurate data and insights from its machine learning and artificial intelligence innovations,” said Sivan Metzger, CEO of ParallelM. “In other industries, we’ve seen the major role machine learning plays in improving outcomes and it is no different in the not-for-profit space.”


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