omega-ml is built to make data science teams effective again. omega-ml's core belief is that data scientists should not have to deal with the complexities of modern day software engineering. Data Science is about making a business more successful, not about technology. 

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That's why omega-ml enables data scientists to be 100% focused on building useful models and deriving value from data. Its innovative approach to vendor- & platform independence means individual data scientists and teams of any size get to have a productive MLOps experience on day 1.

 

The free omega-ml community offering provides a fast opportunity to demonstrate value. For organizations wanting to achieve full AI maturity, omega-ml commercial editions offer advanced integration features such as SSO, user groups, multi tenancy, and deployment options for maximum independence and control, including to your kubernetes, on-prem and hybrid cloud environment.  

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omega-ml timeline

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2025 - Integrated AI Delivery Platform

• Generative AI Integration: Seamless support for generative AI models.

• Support for Third-Party Models: Integration of large language models and external AI models to extend omega-ml’s capabilities.

2024 - Simplifying MLOps further

• User-Friendly UI: Simplified tools for managing, monitoring, and deploying models with transparency and compliance.

• Dashboard: Real-time tracking, drift monitoring, and alerts to keep teams on top of their models.

2022–2023 - Corporate Use Cases

• MLOps goes Corporate: Deployed in Swiss banking and corporate settings, providing SSO integration and custom API support.

• Global Reach: Expanded internationally with cloud-hosted solutions, GPU support, and private tenant cloud deployments.

2018–2021 - MLOps simplified foundation

• Cloud Manager & International Marketing (2020–2021): Introduced Cloud Manager for customizable deployments, expanded to global markets with cloud and GPU support

• Swiss-Hosted SaaS (2019): Launched fully Swiss-based MLOps SaaS platform, with a focus on attaining full vendor independence and enable customers to follow Swiss and EU data privacy laws.

• Open Source Launch (2018): omega-ml was refactored and its core open-sourced under the Apache License 2, enabling community contributions. The license has since been changed to follow the Fair-code Principles, enabling free use with commercial limitations.

• Development of core components (2016): omega-ml was developed for internal use and enabling of collaboration among data scientists inside and across organizations. Already it enabled cloud deployment of machine learning models for mobile applications.