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 (like cloud, docker, kubernetes, security, etc.). 

​

That's why omega-ml enables data scientists to be 100% focused on building useful models and deriving value from data. Our innovative approach to vendor- & platform independence means data scientist teams of any size can 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, the omega-ml commercial edition and our engineering services offer advanced integration features such as SSO, user groups, multi tenancy,  kubernetes and hybrid cloud.  

​

omega-ml timeline

​

2023 - Working on new innovative features to support transparent and data-conscious deployments and collaboration, e.g. for large language
            models and other models provided by third-party. Further planned additions include a web-based dashboard and further
            convenience in deploying smart apps.

​

2022 - Introduction of omega-ml in a Swiss banking institute as the central MLOps platform for all of their sales & marketing ML applications
            and ML operations. The deployment is protected by the bank's Single Sign On (SSO) infrastructure and interfaces with the bank's
            application integration layer, offering OpenAPI-compliant REST APIs to any application, custom-created and deployed with a single line
            of code.

​

2021 - Partner agreement for international distribution with a partner organization and  consulting engagements with Swiss Startups and
            launch of Azure and AWS hosting options. Use of omega-ml in a Gaming Simulation project utilizing GPUs (USA).. 

​

2020 - Introduced the Cloud Manager as the fully customizable deployment platform for omega-ml and all related services, including
            mandated Kubernetes and on-premise deployments. First GPU-enabled deployments for simulation of game playing algorithms
            using deep learning.
 

2019 - Launched the first Swiss-hosted commercial MLOps SaaS platform to fully meet data privacy and data security requirements. First
            applications in USA (consulting company), a Swiss insurance company and a Swiss startup.
 

2018 - Open sourced under the Apache License v2.0. The license was subsequently extended by the "No-Sell, Consulting Yes" Commons
            Clause to avert misuse of omega-ml intellectual property.

​

2016 - Patrick Senti built the core of omega-ml as the internal data science platform for his smart city & next-gen mobility startup launched
            in 2014, where the challenge was to collaborate on large out-of-core datasets between a distributed team of data scientists, and to
            deploy many hundreds of machine learning models for operation in the cloud and integration into a smartphone travel app.