MLOps for AI Vision

Train Better, Faster, and More Efficient!

Our MLOps empower your AI engineers, let you bring your ML models to production, launch products, and updates faster. Whether you're an enterprise looking to automate your processes or a startup in need of a scalable AI solution, our MLOps AI Service can help!

What is MLOps?

MLOps (DevOps for Machine Learning) is a set of principles and practices to enable the automated, continuous delivery and updating of machine learning models. It combines the practices of DevOps and Machine Learning to enable teams to develop, train, and deploy ML models faster, with improved accuracy and confidence.

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What is MLOps?

Components of MLOps

Data Management
Data Management

Ensure that data, the foundation of MLOps, is managed effectively, including data storage, data cleaning, data preprocessing, and data versioning.

Model Deployment
Model Deployment

Involve deploying the trained model in a production environment, making it available for use by end-users. It requires selecting the appropriate infrastructure, containerizing the model, and deploying it to a production environment.

Feedback Loops
Feedback Loops

Allow MLOps teams to continuously improve the model's performance. Feedback can come from end-users, data scientists, or automated systems.

Model Training
Model Training

Include creating, testing, and refining ML models to improve their accuracy and performance. You have to select the appropriate algorithm, tune its hyperparameters, and evaluate the model's performance against various metrics.

Monitoring
Monitoring

Ensure the model is performing as expected after deployment. Various metrics need trackings such as accuracy, latency, and throughput, and triggering alerts.

Collaboration & Governance
Collaboration & Governance

Make sure that all stakeholders (data scientists, developers, and business stakeholders) are aligned and work towards the same goals. This component involves creating clear guidelines and processes for collaboration, version control, and documentation.

What Does Neurond Do?

We offer both MLOps consulting and MLOps development for businesses and organization.

MLOps Consulting

MLOps Consulting
  • List IconScale and avoid potential risks while implementing changes that lead your business to growth.
  • List IconAnalyze the strengths and limitations of the current solution, evaluate the effectiveness of the model, and make recommendations for improvement.
  • List IconSelect and implement model training, scaling techniques, and problem-solving methodologies.
  • List IconChoosing and adopting approaches for model training, scaling methods and problem-solving processes.
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MLOps Development

MLOps Development
  • List IconConcentrate on the implementation itself and carefully organizing the system.
  • List IconAdjust AI solutions to meet the requirements of a certain system or customer. Enhance the solution by focusing on the needs and objectives of the client.
  • Upgrade your team!
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So I guess sending an email would've worked better indeed. And I got logged out on three devices simultaneously.

Automate your ML workflow

Automate your ML workflow

Neurond MLOps manage your entire machine learning pipeline, starting with data preparation to model training and then model deployment. We ease the machine learning integration into your existing workflows by automating the deployment and scaling of your models.

Increase your ML team’s efficiency

Increase your ML team’s efficiency

Our MLOps AI Service provides a centralized platform for managing and collaborating on machine learning projects. With built-in version control and collaboration tools, your team can work more efficiently and effectively.

Ensure the reliability and reproducibility of your models

Ensure the reliability and reproducibility of your models

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Our platform includes tools for tracking and monitoring your models in production, making it easy to identify and address issues. We also provide tools for reproducibility, ensuring that your models can be recreated and tested over time.

Scale your machine learning infrastructure

Scale your machine learning infrastructure

Neurond’s MLOps AI Service is designed to work with any cloud provider, making it easy to scale your machine learning infrastructure as your needs evolve.

MLOPs Across Industries

A wide range of industries can leverage the power of our MLOps services.

Finance

Finance

Help financial institutions develop fraud detection models, credit risk assessment models, and predictive analytics models.

Manufacturing

Manufacturing

Allow manufacturers to develop predictive maintenance models, quality control models, and supply chain optimization models.

E-commerce

E-commerce

Enable e-commerce companies to build recommendation systems, pricing optimization models, and demand forecasting models.

FinTech

Automate and support operations with sensitive data and process tons of data simultaneously.

Why Choose Neurond MLOps Platform

Our enterprise ready MLOps teams have a proven record of stability and performance.

Proactive monitoring

Proactive monitoring

Identify issues arising in infrastructure.

24/7 Support Icon

24/7 support

Provide world-class support during business hours or you need 24x7x365 availability.

Incident management

Incident management

Restore services quickly and ensure issues don’t recur.

Clear communication

Clear communication

With status reporting, weekly technical reviews, and quarterly business reviews, you can keep track of performance and expenses.

FAQs

Got questions about Neurond MLOps? We've got answers.

Unlike other software applications, MLOps is data-driven, dynamic, scalable, collaborative, and compliant. It’s a complex and dynamic field that requires specialized tools and processes to manage the entire machine-learning lifecycle. MLOps platforms provide a way for organizations to build and manage machine learning applications at scale while ensuring that models are accurate, reliable, and compliant.

Controlling costs for ML applications and platforms can be a significant challenge, especially as data sets and models grow in size and complexity. You should optimize your hardware, use cost-effective data storage, automate processes, monitor and optimize resources, and use open-source tools. 

It depends on your organization’s ML requirements and scalability. Our cost varies based on platforms, infrastructure, and applications under support. Contact us for more details on our pricing packages.

Have other questions?

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Revolutionize the way you work. Our goal is to help you be more effective, more creative and push your business further than you thought possible. Our solutions have changed the way companies approach working. Whether that be through bespoke machine learning algorithms, a custom computer vision solution or a tailored forecasting tool, you can be confident we will find the right solution to make an impact.

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