Train, deploy, and confidently operate machine learning models by leveraging rock-solid, cost-effective, and easy-to-use cloud solutions — with Chaos Gears as your comprehensive MLOps partner.
We help design, build, deploy and maintain cost-effective machine learning solutions, providing full-cycle MLOps services.
We provide notebook-based research environments without memory or computing power limitations. All experiments and models remain ready for use long after creation.
We help you leverage the power of compute clusters with GPUs and dedicated filesystems to train and fine-tune even the largest models.
From classic autoscaling APIs, through serverless and asynchronous APIs, to scheduled, large-scale one-off jobs — deploy hundreds of models at a time, in a cost-efficient way.
We ensure that models are working as intended by monitoring the reasonableness of their results and consistency of their data distribution — on top of standard metrics like resource utilization, of course.
We use dedicated CI/CD tools to automate training, deployment and monitoring. New prototypes and models quickly find their way to test and production environments.
We combine top-tier LLMs with a reliable AWS backbone and tools such as LangChain, LLamaindex and vector databases to revolutionize your business processes.
Our engineers are certified experts in their field. In fact, our Data & AI team is led by a prestigious AWS Machine Learning Hero.
We are flexible, but reliability is paramount. We only work with industry-proven, reliable MLOps solutions.
We rely on services from the Amazon SageMaker family, which has parts dedicated to each phase of your data science projects.
Alternatively, we use open-source technologies such as Kubeflow, MLflow or Seldon Core implemented on Kubernetes in AWS.
We help you set the goals, values and essential success criteria. Your data teams can rely on our support with business problem modeling in terms of machine learning and algorithm prototypes.
With our exploratory data analysis ecosystem, we supply you with tools to train, test and tune machine learning models in an automated way.
Your models operate in a production environment. We continuously monitor and verify whether they meet key assumptions and goals through A/B tests and retraining algorithms based on the most recent data.
Make full use of your organization's data without the privacy and security concerns of third-party platforms.
Learn how we can helpIn order to deliver AI-powered solutions that perfectly align with your objectives, we work together to uncover GenAI opportunities with the highest ROI. With a reliable foundation in AWS and custom tooling, we can then iterate rapidly to deliver bespoke projects fine-tuned to your needs.
Your data can stay completely in your own environment. Beyond the confidentiality guarantees of Amazon Bedrock, we can restrict model use to vetted, fully open source foundation models and host them on your own AWS account. We can also restrict the project to services and tools that prohibit any third-party access to your data.
We'd love to answer your questions and help you unify, automate and optimize your machine learning operations.