Chicago, July 09, 2024 (GLOBE NEWSWIRE) -- The ModelOps Market is projected to reach expected to grow from USD 5.4 billion in 2024 to USD 29.5 billion in 2029, at a CAGR of 40.2% during the forecast period,
ModelOps, or Model Operations, is a set of practices and tools used to manage and operationalize machine learning models in a production environment. This includes deploying, monitoring, maintaining, and governance models to ensure they perform as expected. ModelOps aims to streamline the lifecycle of models, from development to deployment and beyond, ensuring they remain reliable, scalable, and compliant with regulatory requirements. By integrating modelOps into an organization’s workflow, businesses enhance their ability to derive value from data-driven insights while maintaining robust oversight and control over their machine learning initiatives.
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ModelOps Market Dynamics:
Drivers:
- Facilitates a seamless pipeline for ML model development, deployment, and monitoring.
- Harmonizes workflows across data science and IT operations domains.
- Reduces time-to-market and minimizes errors in model deployment.
Restraints:
- Achieving interpretability without sacrificing performance is challenging, especially for complex models like deep neural networks.
- Simplifying models for interpretability often reduces predictive power and effectiveness.
Opportunities:
- Revolutionizes the ModelOps market by operationalizing and managing ML models more efficiently.
- Streamlines testing, validation, and deployment processes, reducing human errors and accelerating time-to-market.
List of Key Players in ModelOps Market:
- IBM (US)
- Google (US)
- Oracle (US)
- SAS Institute (US)
- AWS (US)
- Teradata (US)
- Palantir (US)
- Veritone (US)
- Altair (US)
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Based on the offering, the ModelOps Market has been segmented into platforms and services. The platforms segment has been bifurcated by type and deployment mode. Based on the platform by type, the market is divided into development & experimentation platforms, monitoring & observability tools, automated machine learning (AutoML) platforms, performance tracking & management platforms, model explainability & interpretability tools, serving & deployment tools, and others. Based on deployment mode, the market is segmented into clouds and on-premises. Services are segmented into consulting, deployment & integration, and support & maintenance.
The model type segment is bifurcated into ML models, graph-based models, rule & heuristic models, linguistic models, agent-based models, bring-your-own models, and other model types. The ModelOps market categorizes models by type to streamline operational processes and deployment strategies tailored to each model type's specific characteristics and requirements. This segmentation enables efficient management, monitoring, and optimization of models throughout their lifecycle, ensuring robust performance and business impact.
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The ModelOps market, centered around operationalizing machine learning models, spans various applications. By applications, the market is divided into continuous integration/continuous deployment, batch scoring, governance, risk, and compliance, parallelization and distributed computing, monitoring and alerting, dashboard and reporting, model lifecycle management, and others.
The vertical segment is divided into BFSI, retail & ecommerce, healthcare & life sciences, telecommunications, IT/ITES, energy & utilities, manufacturing, transportation & logistics, government & defense, and other verticals. Various verticals across industries significantly influence the ModelOps Market, shaping its growth trajectory and adoption patterns. Industries such as healthcare & life sciences, BFSI, retail & consumer goods, manufacturing, and telecommunications increasingly use modelOps solutions to streamline model deployment, monitoring, and management to ensure scalability, reliability, and compliance across diverse industries.
The ModelOps Market has been segmented into five regions: North America, Europe, Asia Pacific, Middle East & Africa, and Latin America. North America is estimated to account for the largest share of the ModelOps market in 2024, followed by Europe. North America is experiencing growth in the ModelOps market due to several factors. The region is home to a high concentration of tech companies, financial institutions, and healthcare providers adopting advanced analytics and AI technologies. Robust investment in cloud infrastructure and data management platforms is essential for scaling ModelOps operations. Additionally, stringent regulatory frameworks necessitate reliable and compliant model deployment and monitoring, further driving North America's demand for ModelOps solutions.
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