{"id":101720,"date":"2024-12-20T07:16:14","date_gmt":"2024-12-20T07:16:14","guid":{"rendered":"https:\/\/www.globallogic.com\/latam\/?post_type=tech-capabilities&p=101720"},"modified":"2025-02-04T09:10:35","modified_gmt":"2025-02-04T09:10:35","slug":"mlops","status":"publish","type":"tech-capabilities","link":"https:\/\/www.globallogic.com\/latam\/technology-capabilities\/mlops\/","title":{"rendered":"MLOps"},"content":{"rendered":"\r\n\r\n
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Accelerate time-to-market, improve model quality,<\/span> and boost operational efficiency<\/span> for deploying and maintaining ML models.<\/h2> \r\n
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GlobalLogic MLOps solution helps a large UK bank save between \u00a31 million and \u00a33 million every year.<\/p>\n Learn more<\/a>\r\n <\/div>\r\n <\/div>\r\n <\/div>\r\n<\/section>\r\n\n\n\r\n\r\n

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How we help<\/div>\r\n

Accelerate the ML development lifecycle<\/h2>\r\n <\/div>\r\n
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GlobalLogic helps you bridge the gap between data science and IT operations teams using MLOps so that ML\/GenAI models are deployed quickly and reliably, scale efficiently, and deliver accurate predictions over time.<\/p>\r\n <\/div>\r\n <\/div>\r\n

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Our capabilities<\/div>\r\n
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Efficient. Scalable. Reliable.<\/h2>\r\n <\/div>\r\n
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Rapidly and reliably develop, test, deploy and operationalize ML\/GenAI models.<\/p>\r\n <\/div>\r\n <\/div>\r\n

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Data Preparation and Feature Management<\/h3>\r\n

Data is automatically ingested from various sources, cleaned, and transformed into consistent, high-quality data sets for model training. A centralized repository for reusable features improves collaboration and accelerates model development cycles.<\/p> <\/div>\r\n <\/div>\r\n <\/div>\r\n

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Model Development and Deployment<\/h3>\r\n

Automated training streamlines model creation and enables rapid experimentation and tuning. Deployment automation seamlessly transitions models from development to production using canary releases, model comparisons, and versioning to ensure only the best models progress to deployment.<\/p> <\/div>\r\n <\/div>\r\n <\/div>\r\n

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Continuous Monitoring and Improvement<\/h3>\r\n

Performance monitoring includes real-time tracking of model accuracy and efficiency while automated retraining updates models based on performance metrics to keep models accurate. Governance and compliance rules enforce data privacy and security policies. <\/p> <\/div>\r\n <\/div>\r\n <\/div>\r\n <\/div>\r\n

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Engineering insights<\/div>\r\n

Improving Digital Transformation Outcomes with Hyperautomation<\/h2>\r\n <\/div>\r\n
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Discover how integrating digital technology across your organization can help you enhance efficiency, reduce costs, and adapt to future challenges.<\/p>\r\n Learn More<\/a>\r\n <\/div>\r\n <\/div>\r\n

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Our work<\/div>\n
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Case studies<\/h2>\n <\/div>\n
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Discover how we\u2019re engineering impact with clients around the world.<\/p>\n View all our case studies<\/a>\n <\/div>\n <\/div>\n

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From Legacy to Leading-edge: A Global Software Leader\u2019s AI-Driven Angular Migration<\/p>\n <\/div>\n \"GlobalLogic\"\n <\/a>\n <\/div>\n

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Streamlining API Documentation with GenAI-Enabled Automation<\/p>\n <\/div>\n \"GlobalLogic\"\n <\/a>\n <\/div>\n

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Streamlining the SDLC for a Leader in Global Energy Technology<\/p>\n <\/div>\n \"GlobalLogic\"\n <\/a>\n <\/div>\n \n <\/div>\n

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Leaders in MLOps<\/h2>\r\n <\/div>\r\n
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Meet the leaders in MLOps globally.<\/p>\r\n <\/div>\r\n <\/div>\r\n

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\r\n Dr. Nishanthan Kamaleson<\/span>\r\n

Senior Consultant specializing in MLOps Engineering<\/p>\r\n <\/div>\r\n \r\n

Taking complex data and making it easy to understand using advanced AI and data science.<\/h4>\r\n <\/div>\r\n <\/div>\r\n <\/div>\r\n
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\r\n Dr. Jos\u00e9 Albornoz<\/span>\r\n

Principal Consultant, Data Science practice<\/p>\r\n <\/div>\r\n \r\n

Providing practical MLOps solutions through a cross-disciplinary approach to problem solving.<\/h4>\r\n <\/div>\r\n <\/div>\r\n <\/div>\r\n
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\r\n Afroz Shaikh<\/span>\r\n

Principal MLOps Engineer<\/p>\r\n <\/div>\r\n \r\n

Specializing in building MLOps solutions using advanced cloud services and orchestration frameworks.<\/h4>\r\n <\/div>\r\n <\/div>\r\n <\/div>\r\n <\/div>\r\n <\/div>\r\n <\/div>\r\n <\/section>\r\n\n\n
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Featured insights<\/h2>\n <\/div>\n <\/div>\n
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Explore fresh thinking from GlobalLogic’s strategists and engineers.<\/p>\n See all<\/a>\n <\/div>\n <\/div>\n\n

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Blogs<\/div>
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\n\n Michael Lewandowski<\/span><\/a>\n <\/div>\n\n \n 17 diciembre 2025 <\/span>\n <\/div>\n

\n \n Ingenier\u00eda para el cambio: c\u00f3mo las plataformas adaptativas definir\u00e1n el … <\/a>\n <\/h3>\n
\n AI-Powered SDLC<\/span>GenAI<\/span>Financial Services<\/span> <\/div>\n <\/div>\n \n \"Ingenier\u00eda <\/a>\n <\/div>\n <\/div>\n
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Blogs<\/div>
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\n\n Mike Connors<\/span><\/a>\n <\/div>\n\n \n 16 diciembre 2025 <\/span>\n <\/div>\n

\n \n M\u00e1s all\u00e1 de las palabras de moda: por qu\u00e9 \u00abc\u00f3digo, capital y cambio\u00bb es un … <\/a>\n <\/h3>\n

Durante los \u00faltimos meses, en conversaciones con empresas de los sectores …<\/p>\n

\n AI-Powered SDLC<\/span>GenAI<\/span>Financial Services<\/span> <\/div>\n <\/div>\n \n \"M\u00e1s <\/a>\n <\/div>\n <\/div>\n
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Blogs<\/div>
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\n\n Vivek Daga<\/span><\/a>\n <\/div>\n\n \n 16 diciembre 2025 <\/span>\n <\/div>\n

\n \n Capital, reinventado: dise\u00f1ando la pr\u00f3xima frontera del valor en los servicios … <\/a>\n <\/h3>\n

Cuando hablamos del capital como parte de las 3 C (capital, control y control) …<\/p>\n

\n AI-Powered SDLC<\/span>GenAI<\/span>Transformation Advisory<\/span>Financial Services<\/span> <\/div>\n <\/div>\n \n \"Capital, <\/a>\n <\/div>\n <\/div>\n \n <\/div>\n
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FAQs<\/div>\r\n
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Your MLOps questions, answered<\/h2>\r\n <\/div>\r\n
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Learn more about MLOps at GlobalLogic.<\/p>\r\n <\/div>\r\n <\/div>\r\n

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    What is MLOps?<\/div><\/div>\r\n
    MLOps, short for Machine Learning Operations, refers to MLOps solutions, MLOps services, and MLOps platforms that integrate machine learning models into the software development and operations lifecycle. MLOps solutions aim to streamline and automate the deployment, monitoring, management, and governance of machine learning models in production environments.<\/div>\r\n <\/li>\r\n
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    What\u2019s the difference between GenAIOps and MLOps?<\/div><\/div>\r\n
    MLOps is the practice of applying DevOps principles to streamline the development, deployment, monitoring, governance and maintenance of ML models in production, while GenAIOps is the practice of applying an MLOps platform to GenAI systems to streamline the development, deployment, governance, and maintenance of GenAI applications in production. MLOps solutions provide the foundational infrastructure, best practices, and automation tools that GenAIOps builds upon and extends to address the unique challenges of building applications using generative AI.\r\n<\/div>\r\n <\/li>\r\n
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    How does an MLOps framework bridge the gap between Data Science and IT Operations?<\/div><\/div>\r\n
    An MLOp framework bridges the gap between Data Science and IT operations teams with practices, tools, and processes that facilitate ML model deployment and management for MLOps engineers. It aims to automate deployment, ensure model quality, and meet business and regulatory requirements.<\/div>\r\n <\/li>\r\n
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    What does an MLOps consulting service provide?<\/div><\/div>\r\n
    MLOps consulting services provide the expertise and guidance of experienced MLOps engineers to create MLOps frameworks\/MLOps architectures and MLOps platforms that streamline machine learning workflows and improve the efficiency, scalability, and reliability of AI\/ML projects.<\/div>\r\n <\/li>\r\n
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    What is MLOps as a service?<\/div><\/div>\r\n
    MLOps as a service refers to a set of practices and solutions that help businesses effectively manage and automate machine learning workflows, from model development to deployment, monitoring, and maintenance. This can be offered as an MLOps managed service or an MLOPs platform that integrates with existing infrastructure, enabling organizations to streamline AI\/ML projects for more efficient and scalable operations.<\/div>\r\n <\/li>\r\n <\/ul>\r\n <\/div>\r\n <\/section>\r\n","protected":false},"excerpt":{"rendered":"

    Streamline and automate the deployment, monitoring, management, and governance of ML models using MLOps.<\/p>\n","protected":false},"author":1,"featured_media":101727,"parent":0,"menu_order":0,"template":"","work-with-us-category":[],"class_list":["post-101720","tech-capabilities","type-tech-capabilities","status-publish","has-post-thumbnail","hentry"],"acf":[],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/www.globallogic.com\/latam\/wp-json\/wp\/v2\/tech-capabilities\/101720","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.globallogic.com\/latam\/wp-json\/wp\/v2\/tech-capabilities"}],"about":[{"href":"https:\/\/www.globallogic.com\/latam\/wp-json\/wp\/v2\/types\/tech-capabilities"}],"author":[{"embeddable":true,"href":"https:\/\/www.globallogic.com\/latam\/wp-json\/wp\/v2\/users\/1"}],"version-history":[{"count":2,"href":"https:\/\/www.globallogic.com\/latam\/wp-json\/wp\/v2\/tech-capabilities\/101720\/revisions"}],"predecessor-version":[{"id":101729,"href":"https:\/\/www.globallogic.com\/latam\/wp-json\/wp\/v2\/tech-capabilities\/101720\/revisions\/101729"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.globallogic.com\/latam\/wp-json\/wp\/v2\/media\/101727"}],"wp:attachment":[{"href":"https:\/\/www.globallogic.com\/latam\/wp-json\/wp\/v2\/media?parent=101720"}],"wp:term":[{"taxonomy":"work-with-us-category","embeddable":true,"href":"https:\/\/www.globallogic.com\/latam\/wp-json\/wp\/v2\/work-with-us-category?post=101720"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}