The cost-effective and easy-to-use machine-learning platform

At Chaos Gears, we deliver a research environment primed for data exploration and model training by data science teams. The production environment is ready for model deployment with ML-aware monitoring included

Your Data Science projects supported by Chaos Gears


Solution architecture

Our team helps you set the goals, values and essential metrics which allow us to measure success criteria. Your data teams can rely on us to support business problem modeling in terms of machine learning and algorithm prototypes.


Models building and development

With our exploratory data analysis ecosystem, we supply you with tools to validate and tune machine learning models.


Implementations and operations

Your models operate in a production environment, and we continuously monitor and verify whether they meet key assumptions. From A/B tests and retraining algorithms based on the most recent data, we can help monitor them and identify if they no longer meet the goals.

Our offer accelerate the lifecycle of ML projects

We provide our clients with professional services at any stage of their analytics projects. By choosing Chaos Gears, you obtain ready-to-work, cost-effective and versatile platforms dedicated to Data Science teams


You can choose from the proven technologies

The technology market has many products to offer to resolve the data team's daily challenges. At Chaos Gears, we're pragmatic. Based on our experience, we select and use only reliable products with an established position in the market. We use AWS solutions and/or open-source technologies that match your needs

StageMaker Grafika
aws service

Cost-optimized MLOps platform for faster implementation

We rely on services from the Amazon SageMaker family. It has dedicated parts for each phase of your data science projects.

  • One of the most mature cloud technologies in the ML area
  • Low solution maintenance costs
  • Rapid platform deployment
  • Does not require a dedicated maintenance team
Open Source Technologie Grafika

Independent from the cloud providers

We use open-source technologies implemented on the Kubernetes platform on EC2 virtual machines.

  • We use mature and proven technologies such as Kubeflow, MLflow, Seldon Core
  • A solution dedicated to various models (multi-cloud, hybrid-cloud, on-premises)
  • No risk of vendor lock-in
  • Easy migration to another cloud solution in the future

The proof that we speed up MLOps projects

Chaos Gears specialists can boast AWS certificates that confirm our proficiency in the ML area and AWS cloud

AWS Certified - Machin Learing
AWS Certified Solutions Architect Professional
AWS Certified DevOps Engineer Professional
Aws Certified Security Specialty
Cooperation stages

Starting with a series of initial meetings to get to know the team and the operational problems it faces in the field of data analysis, as well as the key goals it aims to achieve.

Based on the collected information, together we select suitable technologies and create an implementation schedule and the project's long-term roadmap.

We determine a list of required components, prioritize it and define the timeframe and delivery of each component (e.g. register of experiments and models, feature store, research environment based on notebooks, automation and orchestration platform, or model implementation system).

You are guaranteed a high level of cloud environment security by building solid cloud foundations for your operations through the creation and configuration of AWS accounts, network services, budget alerts and access management.

Then, in accordance with the set priorities, we deliver the individual components of the MLOps platform. In the case of unknown or unspecified requirements, we create Proof of Concept solutions first. This allows us to verify if the tool's functionality meets your needs.

Quality control is kept through regular contact with the client's data science team to collect further requirements for the platform. We document the process of implementing components on an ongoing basis, demonstrate the products used and conduct training across the whole process on a regular basis.

Along with the management of your production environment, we provide comprehensive maintenance services ensuring that data analysis teams can work efficiently and effectively.

Tools are updated on an ongoing basis, as well as modifying and optimizing the platform when required.

We also correct any errors that were not detected during the tests.