Don't waste another minute with repetitive tasks and focus on improving your IT business! Use ActiveEon, award winning SOAP software & ML data pipeline automation.
ProActive Workflows & Scheduling
Drive efficiency, reduce costs and automate operations from simple tasks to complex processes.
ProActive AI Orchestration
Industrialize your processes, accelerate the AI deployment and improve your AI success rate.
Products Updates, September 2022
Discover all new features, expansions, and hot fixes as released in the products' latest versions.
Orchestrate automation across all ERP, ITSM, ETL/ELT, and across your hydrid environment.
Why ActiveEon is Better & Faster
ActiveEon provides the most advantageous, efficient and fastest solutions.
Powerful and easy workflow management software for IT automation.
Automatically execute IT and business processes on hybrid cloud and on-premises resources, provide self-service portal and reduce support cost.
Hybrid IT Enabler
Maintain a centralized approach to IT governance while exploiting the benefits of cloud computing.
Gain additional flexibility to deal with peaks in IT demand by accessing to more computing resources when needed.
Enable process automation across your entire enterprise and hybrid cloud infrastructure.
Acceleration of Algorithms
Deliver big data and algorithm outcomes faster, scale your resources and use your computing power to the full.
Monitor & Industrialize Processes
Be efficient in operating and monitoring workload automation - and enable self-service for problem resolution.
Minimize the complexity of AI with repeatable & scalable machine learning life-cycle.
Provides a center of excellence for the production of your AI models.
Higher Education & AI
Use your existing ICT infrastructure and improve AI/ML delivery with ActiveEon.
We provide the most reliable tools to make sure you benefit from a smooth and successful migration that matches your needs and gives you a competitive edge.
ActiveEon Smart Migration Process
Learn more about how to easily switch from your old legacy automation solution to ActiveEon.
Migrate from Dollar Universe
Find out how ActiveEon can help you migrate from Dollar Universe and advantageously improve your process automation.
Discover our dedicated SaaS platform for Job Scheduling and Machine Learning.
Take a look at our documentation to understand the technical aspects of our Workflows & Scheduling and Machine Learning solutions.
Learn how to use our ProActive Workflows & Scheduling and ProActive AI Orchestration in 5 training sessions.
See how to orchestrate Automation Across all ERP, ITSM, ETL/ELT, and Across your Hybrid Cloud.
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Learn more about workload orchestration, job scheduling, IT automation and machine learning!
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ActiveEon is the new automation solution of choice. Learn about who we are and what we stand for.
ActiveEon displaces legacy solutions in worklflow automation by designing state-of-the-art software solutions. See more about our company vision and values.
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Simplify, accelerate & industrialize machine learning with an open platform. Seamlessly execute at any scale in production with any data source, on any infrastructure.
ProActive AI Orchestration from Activeeon empowers data engineers and data scientists with a simple, portable and scalable solution for machine learning pipelines. It provides pre-built and customizable tasks that enable automation within the machine learning lifecycle, which helps data scientists and IT Operations work together.
The product fully supports Machine Learning Operations (MLOps).
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ProActive AI Orchestration includes Machine Learning Open Studio (MLOS): compose ML workflows with drag & drop
Data connector tasks & workflows templates help to automate and scale up data ingestion and data preparation pipelines
Scale up parallel model training, validation and testing
AutoML to scale up the model tuning during experiments
Jupyter Kernel & Python connector to create AI workflows from code
AI tasks & workflow templates to automate AI pipelines
Model as a Service (MaaS): deploy and expose AI models in production; scale up model deployment; monitoring, alerting, data drift detection
JupyterLab as a Service: deploy a JupyterLab instance on-demand
Job analytics & visualization as a Service: track and visualize metrics of your machine learning workflow
Managed Services (KNIME, …)
In one click, securely open typical interactive AI services such as JupyterLab, TensorBoard, Visdom, COCO_Annotator, H2O GUI, Knime, etc.
ProActive workflows enable data engineers, data scientists and IT Operations to create and automate pipelines so that results could be reliable and consistent across execution. Users can execute entire machine learning pipelines with confidence and in any environment, from development to production, and on any infrastructure, from CPU to GPU and FPGA.
Portability is key to ensure no vendor lock in and promote collaboration between users. It is also critical to scale. The workflows and algorithms created need to access any infrastructure setup (on-prem, hybrid, multi-cloud, HPC, edge, etc.) and leverage the whole compute capacity from CPU to GPU / TPU / FPGA.
Activeeon solutions include a resource manager that abstracts away the resources and offers this portability. Some smart policies can also be configured to trigger auto-scaling based on the actual scheduler queue.
The machine learning ecosystem is constantly evolving and its open source community is strong. The ability to leverage those contributions is key to ensure constant up to date techniques and best performances. ProActive AI Orchestration is open from end to end and support those needs.
Moreover, some steps of the machine learning process are quite repetitive and can be made generic. ProActive AI Orchestration includes a catalog solution that enables sharing, versioning and easy reutilization of machine learning models and services (MaaS).
Pipeline & Workflow Orchestration: Edge to Core to Cloud to Edge for AI + HPC
Make deployments and scaling of machine learning models on any infrastructure simple, portable and scalable
Provide a straightforward way to deploy ML systems to diverse infrastructures (local, hybrid, multi-cloud, edge)
Provide a pipeline solution to enable automation within the machine learning lifecycle