The mission of CyberPoint's AIZEN team is to bring Artificial Intelligence solutions to our client's most challenging problems. AI is a critical 21st century technology and our dedicated team of Data Scientists and Machine Learning Engineers bring the knowledge and expertise to help your enterprise realize its fullest potential. We specialize in taking business challenges and translating them into material AI solutions.
Our cross functional team provides services from AI strategy consulting to machine learning model development. We design & implement tools to support machine learning operations (MLOps) that support the deployment, monitoring, and maintenance of AI models in production. Our clients know the value of the operational applications we produce to automate critical business processes, predict outcomes, and reduce business risk.
Our team works with our clients to leverage the potential of Artificial Intelligence and Machine Learning strategies. We help organizations understand how AI can bring transformation to their existing products, solve their most pressing challenges, and demonstrate how their ideas can become reality.
A strong AI strategy requires a roadmap and we've got the playbook. We help our clients answer key questions such as:
Without a clear roadmap, it can be difficult to know what steps to take and when to take them. This can lead to wasted time and resources and can ultimately hinder your project's goals. A well-crafted AI strategy will help you avoid these pitfalls and set your enterprise up for success.
AI model development is the process of creating and training models that can be used to make predictions or recommendations. Our team supports the entire model lifecycle bringing processes, tools, and techniques together to enable the streamlined and efficient delivery of AI models.
That lifecycle includes:
MLOps is the discipline of combining requirements for supporting Machine Learning models with DevSecOps principles. MLOps seeks to provide tools and techniques to support the deployment, monitoring, maintenance, storage, security, and governance of models produced. Our team provides a robust and scalable MLOps reference architecture that enables you to streamline your machine learning workflow and quickly deploy your models into production. Our architecture is designed to handle the complex dependencies and data processing requirements of machine learning applications. By using our best practices, you can increase the speed, quality, and reliability of your machine learning models while reducing the cost and complexity of the process.
Contact us with queries about how we can support your mission today.
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