MLOps & Governance

We support your company in the systematic management of your machine learning projects, taking into account the legal requirements of the EU AI Act.

MLOps as the basis for professional AI applications

MLOps is the central component for the professionalization of ML projects. It encompasses infrastructure and processes throughout the entire ML lifecycle, taking into account MLOps principles. At the same time, MLOps helps to increase the trustworthiness and traceability of solutions and is a step towards compliance with regulations. Once implemented, the foundation for future AI activities is established.

The start of MLOps can quickly become overwhelming because an appropriate selection of necessary tools must be made from a huge range of options. Additionally, many tools come with a long-term commitment to the provider. Optimal utilization of MLOps often requires extensive integration efforts.

Our approach: The open appliedAI MLOps model.

At appliedAI, MLOps means connecting the perspectives and needs of developers, management, and business units.

Our MLOps environment focuses on ease of use and scalability, ranging from local operation on a laptop to a cluster. Centralized data management enables data versioning and validation.

Combining different tools allows for fault tolerance, incremental development, and auditability of the application. Experiment tracking, model versioning, model deployment strategies, monitoring, and application implementation are also possible. In addition, the MLOps environment can support regulatory and governance processes such as portfolio management and business models for companies in the future.

Our offers

We support companies with different offerings and implementation depths

  • Analysis of the current situation and needs through workshops
  • Trainings on MLOps, EU AI Act and use case classification
  • Implementation of the open MLOps environment from appliedAI and various partners

By combining the best available MLOps tools, you can increase the effectiveness and efficiency in your ML lifecycle management. By setting up your development environment according to MLOps principles, you will receive:

  • Provision in an optimized environment
  • Automation of manual steps such as storing logs or results
  • Reproducibility and comparability of training runs

MLOps Workshop Series

The workshops consist of a half-day workshop with a maximum of 10 participants. The workshops can be booked individually or as a package of three. 

The individual price per workshop is 4,000 euros, and the package price for all three workshops is 12,000 euros. The workshops are led by one of our appliedAI experts.

1 Introduction to MLOps expand_more

The goal of the workshop "Introduction to MLOps" is to provide basic knowledge within your team and to have a subsequent discussion about MLOps.

The workshop introduces the concepts, principles, and best practices of MLOps in companies. 

The following topics will be covered:

  • Motivation for MLOps
  • AI project management and ML lifecycle
  • MLOps concepts and principles
  • Challenges and best practices
  • Overview of the AppliedAI toolchain for MLOps
  • Discussion about governance and regulations
2 Maturity levels in MLOps expand_more

The "MLOps Maturity Assessment" is a structured evaluation of the current state, the desired state, and the out-of-scope MLOps activities in your company, building upon the "Introduction to MLOps" workshop.

Overview of main topics:

  • Definition of MLOps challenges in the areas of: 
    • Scoping
    • Data management 
    • Modeling 
    • Deployment and DevOps
  • Assessment of maturity level in each of the domains
  • Prioritization of MLOps activities
3 Target Image and Roadmap expand_more

The workshop "Target Vision and Roadmap" builds on the results of the two previous workshops. The workshop aims to define the MLOps target vision and create a roadmap for implementing any missing MLOps tools and functions in your company.

Overview of topics covered:

Consolidation of the MLOps target vision by defining milestones for creating the MLOps roadmap: establishing the goal and activities considering that value should be generated for the company.

Our offer in the context of the AI Act

Introduction training on the AI Act

The EU AI Act will have far-reaching implications for the entire AI ecosystem. Therefore, it is important that companies are aware of what the new law means for them. The introduction training on the AI Act is relevant for all employees of a company who are involved in the development or application of AI applications. The training is conducted by an appliedAI expert in English and lasts 1-1.5 hours.

Workshop Risk Classification

Depending on the risk class of its AI use cases, a company must comply with different strict requirements. To support use case teams in categorizing their applications, the workshop offers a structured and comprehensive insight into the necessary steps to comply with the AI Act. At the end of the workshop, participants will receive a risk classification result per use case.

The interactive training is conducted by an appliedAI expert in English and lasts 3-4 hours. Participants can complete the workshop online or in person.

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