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MLOps

Our team of experienced professionals is here to help your organization take advantage of the latest Machine Learning (ML) Practices and Technologies.

MLOps

Overview of Service

With our MLOps services, you can streamline your ML development and deployment processes, and bring new features and updates to your customers faster and more reliably.

What we Offer

Native Apps

Automated Infrastructure & Deployment Processes

Hybrid Apps

CI/CD Implementation

Web Apps

Monitor & Log Your Application

Web Apps

Containerize Your Applications

Web Apps

Automated Testing

Our Approach

01

Machine Learning

We use machine learning algorithms and their applications, with the ability to implement and fine-tune models.

    02

    Automation

    We use automation tools to manage ML infrastructure and deploy models, such as Kubernetes, Docker, and Git.

      03

      Continuous Integration and Continuous Delivery

      Our team is experienced in setting up and maintaining CI/CD pipelines for ML models, and knowledge of best practices for testing and deploying models.

        04

        Model Management

        We use model management techniques such as versioning, rollback and roll forward, and able to implement them.

          05

          Data Engineering

          Our team is familiar with Data Engineering concepts, data pipeline creation, data storage and data.

            06

            Communication and Collaboration

            Strong communication and collaboration skills are essential in a MLOps environment, as it involves close collaboration between data scientists and operations teams.

              Technologies Technologies we use

              ML flow

              ML flow

              DVC

              DVC

              Neptune.ai

              Neptune.ai

              Wandb

              Wandb

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