Machine learning lifecycle management and ML-Ops technology enables “Work from Home” data science
Tel Aviv – June 23, 2020 –Israeli Company Allegro AI, the leading provider of end-to-end ML/DL lifecycle management and ML-Ops solutions, has doubled its active userbase over the past three months. Meanwhile, overall IT spending on a global basis decreased by more than 8 percent during the same period.
Available in both open-source and enterprise versions, Allegro Trains enables data science and data engineering teams to easily develop and scale their AI model training. Its versioning, logging, comparison, and sharing features ensure teams can collaborate effectively and leverage other colleagues’ work efficiently from anywhere – especially relevant during the COVID-19 related remote work reality.
Allegro Trains’ active userbase doubled over the past three months, driven by new organizations ranging from start-ups to Fortune 100 companies hailing from some 50 countries across the globe – even from far-off places such as Mongolia – and representing industries ranging from automotive to medical imaging and manufacturing to media.
Allegro AI provides an open-source full solution to manage development and deployment of AI models. Its signature “automagical” dead simple integration and zero workflow changes required, enables teams to start seeing value from Allegro Trains within minutes to hours, all while continuing to work in their preferred workflows.
The enterprise version’s managed services and sophisticated data and metadata management tools enable organizations to scale development and deployment. Powerful analytics tools and data debiasing capabilities allow them to take control of their data. The platform supports continuous learning, active learning, transfer learning, and federated learning at scale.
“Demonstrating such major growth, particularly during a crisis, really highlights the ease of use and integration of Allegro Trains,” said Nir Bar-Lev, CEO of Allegro AI. “Being able to be productive and collaborate efficiently has always been important for AI teams, and the ‘work from home’ reality has only driven that need further. We’re proud that we have been able to help our customers continue to be productive and deliver innovation in AI for their users.”
