Find and compare the best Artificial Intelligence software for ModelOp in 2025
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Use the comparison tool below to compare the top Artificial Intelligence software for ModelOp on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
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Google Cloud Platform
Google
Free ($300 in free credits) 60,418 RatingsThe Google Cloud Platform (GCP) offers a comprehensive collection of Artificial Intelligence (AI) and machine learning resources aimed at simplifying data analysis processes. It features a range of pre-trained models and APIs, including Vision AI, Natural Language, and AutoML, enabling businesses to effortlessly integrate AI into their applications without needing extensive knowledge of the subject. New users are also granted $300 in complimentary credits to experiment with, test, and implement workloads, allowing them to investigate the platform's AI functionalities and develop sophisticated machine learning applications without any upfront investment. GCP’s AI offerings are designed to work harmoniously with other services, facilitating the creation of complete machine learning workflows from data management to model deployment. Moreover, these tools are built for scalability, empowering organizations to explore AI and expand their AI-driven solutions as their requirements evolve. With these capabilities, companies can swiftly adopt AI for a variety of applications, including predictive analysis and automation. -
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Teradata VantageCloud
Teradata
975 RatingsTeradata VantageCloud: Open, Scalable Cloud Analytics for AI VantageCloud is Teradata’s cloud-native analytics and data platform designed for performance and flexibility. It unifies data from multiple sources, supports complex analytics at scale, and makes it easier to deploy AI and machine learning models in production. With built-in support for multi-cloud and hybrid deployments, VantageCloud lets organizations manage data across AWS, Azure, Google Cloud, and on-prem environments without vendor lock-in. Its open architecture integrates with modern data tools and standard formats, giving developers and data teams freedom to innovate while keeping costs predictable. -
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TensorFlow
TensorFlow
Free 2 RatingsTensorFlow is a comprehensive open-source machine learning platform that covers the entire process from development to deployment. This platform boasts a rich and adaptable ecosystem featuring various tools, libraries, and community resources, empowering researchers to advance the field of machine learning while allowing developers to create and implement ML-powered applications with ease. With intuitive high-level APIs like Keras and support for eager execution, users can effortlessly build and refine ML models, facilitating quick iterations and simplifying debugging. The flexibility of TensorFlow allows for seamless training and deployment of models across various environments, whether in the cloud, on-premises, within browsers, or directly on devices, regardless of the programming language utilized. Its straightforward and versatile architecture supports the transformation of innovative ideas into practical code, enabling the development of cutting-edge models that can be published swiftly. Overall, TensorFlow provides a powerful framework that encourages experimentation and accelerates the machine learning process. -
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Docker streamlines tedious configuration processes and is utilized across the entire development lifecycle, facilitating swift, simple, and portable application creation on both desktop and cloud platforms. Its all-encompassing platform features user interfaces, command-line tools, application programming interfaces, and security measures designed to function cohesively throughout the application delivery process. Jumpstart your programming efforts by utilizing Docker images to craft your own distinct applications on both Windows and Mac systems. With Docker Compose, you can build multi-container applications effortlessly. Furthermore, it seamlessly integrates with tools you already use in your development workflow, such as VS Code, CircleCI, and GitHub. You can package your applications as portable container images, ensuring they operate uniformly across various environments, from on-premises Kubernetes to AWS ECS, Azure ACI, Google GKE, and beyond. Additionally, Docker provides access to trusted content, including official Docker images and those from verified publishers, ensuring quality and reliability in your application development journey. This versatility and integration make Docker an invaluable asset for developers aiming to enhance their productivity and efficiency.
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Jira
Atlassian
Free 44 RatingsJira is a project management tool that allows you to plan and track the work of your entire team. Atlassian's Jira is the #1 tool for software development teams to plan and build great products. Jira is trusted by thousands of teams. It offers a range of tools to help plan, track, and release world-class software. It also allows you to capture and organize issues, assign work, and follow team activity. It integrates with leading developer software for end-toend traceability. Jira can help you break down big ideas into manageable steps, whether they are small projects or large cross-functional programs. Organize your work, create milestones and dependencies, and more. Linking work to goals allows everyone to see how their work contributes towards company objectives, and to stay aligned with what's important. Your next step, suggested by AI. Atlassian Intelligence automatically suggests tasks to help you get your big ideas done. -
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Microsoft Azure
Microsoft
21 RatingsMicrosoft Azure serves as a versatile cloud computing platform that facilitates swift and secure development, testing, and management of applications. With Azure, you can innovate purposefully, transforming your concepts into actionable solutions through access to over 100 services that enable you to build, deploy, and manage applications in various environments—be it in the cloud, on-premises, or at the edge—utilizing your preferred tools and frameworks. The continuous advancements from Microsoft empower your current development needs while also aligning with your future product aspirations. Committed to open-source principles and accommodating all programming languages and frameworks, Azure allows you the freedom to build in your desired manner and deploy wherever it suits you best. Whether you're operating on-premises, in the cloud, or at the edge, Azure is ready to adapt to your current setup. Additionally, it offers services tailored for hybrid cloud environments, enabling seamless integration and management. Security is a foundational aspect, reinforced by a team of experts and proactive compliance measures that are trusted by enterprises, governments, and startups alike. Ultimately, Azure represents a reliable cloud solution, backed by impressive performance metrics that validate its trustworthiness. This platform not only meets your needs today but also equips you for the evolving challenges of tomorrow. -
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Microsoft Power BI
Microsoft
$10 per user per month 8 RatingsPower BI provides advanced data analysis, leveraging AI features to transform complex datasets into visual insights. It integrates data into a single source, OneLake, reducing duplication and streamlining analysis. The platform enhances decision-making by integrating insights into everyday tools like Microsoft 365 and is bolstered by Microsoft Fabric for data team empowerment. Power BI is scalable, handling extensive data without performance loss, and integrates well with Microsoft's ecosystem for coherent data management. Its AI tools are user-friendly and contribute to efficient and accurate insights, supported by strong data governance measures. The Copilot function in Power BI enables quick and efficient report creation. Power BI Pro licenses individuals for self-service analytics, while the free account offers data connection and visualization capabilities. The platform ensures ease of use and accessibility, backed by comprehensive training. It has shown a notable return on investment and economic benefits, as reported in a Forrester study. Gartner's Magic Quadrant recognizes Power BI for its ability to execute and completeness of vision. -
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Snowflake offers a unified AI Data Cloud platform that transforms how businesses store, analyze, and leverage data by eliminating silos and simplifying architectures. It features interoperable storage that enables seamless access to diverse datasets at massive scale, along with an elastic compute engine that delivers leading performance for a wide range of workloads. Snowflake Cortex AI integrates secure access to cutting-edge large language models and AI services, empowering enterprises to accelerate AI-driven insights. The platform’s cloud services automate and streamline resource management, reducing complexity and cost. Snowflake also offers Snowgrid, which securely connects data and applications across multiple regions and cloud providers for a consistent experience. Their Horizon Catalog provides built-in governance to manage security, privacy, compliance, and access control. Snowflake Marketplace connects users to critical business data and apps to foster collaboration within the AI Data Cloud network. Serving over 11,000 customers worldwide, Snowflake supports industries from healthcare and finance to retail and telecom.
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OpenAI aims to guarantee that artificial general intelligence (AGI)—defined as highly autonomous systems excelling beyond human capabilities in most economically significant tasks—serves the interests of all humanity. While we intend to develop safe and advantageous AGI directly, we consider our mission successful if our efforts support others in achieving this goal. You can utilize our API for a variety of language-related tasks, including semantic search, summarization, sentiment analysis, content creation, translation, and beyond, all with just a few examples or by clearly stating your task in English. A straightforward integration provides you with access to our continuously advancing AI technology, allowing you to explore the API’s capabilities through these illustrative completions and discover numerous potential applications.
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Keras is an API tailored for human users rather than machines. It adheres to optimal practices for alleviating cognitive strain by providing consistent and straightforward APIs, reducing the number of necessary actions for typical tasks, and delivering clear and actionable error messages. Additionally, it boasts comprehensive documentation alongside developer guides. Keras is recognized as the most utilized deep learning framework among the top five winning teams on Kaggle, showcasing its popularity and effectiveness. By simplifying the process of conducting new experiments, Keras enables users to implement more innovative ideas at a quicker pace than their competitors, which is a crucial advantage for success. Built upon TensorFlow 2.0, Keras serves as a robust framework capable of scaling across large GPU clusters or entire TPU pods with ease. Utilizing the full deployment potential of the TensorFlow platform is not just feasible; it is remarkably straightforward. You have the ability to export Keras models to JavaScript for direct browser execution, transform them to TF Lite for use on iOS, Android, and embedded devices, and seamlessly serve Keras models through a web API. This versatility makes Keras an invaluable tool for developers looking to maximize their machine learning capabilities.
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ServiceNow
ServiceNow
$100 per month 1 RatingEmbrace digital workflows and watch your team flourish. By leveraging advanced solutions, your organization can enhance productivity and foster greater employee engagement. ServiceNow revolutionizes the way work is done, transforming outdated manual processes into efficient digital workflows, ensuring that both employees and customers receive prompt and seamless support. With ServiceNow, you gain access to digital workflows that not only enhance user experiences but also boost overall productivity for both staff and the organization as a whole. Our platform streamlines work complexities through a unified cloud system, known as the Now Platform: an intelligent and user-friendly solution tailored for modern work environments. You can select from our pre-designed workflows or craft custom applications tailored to your needs. Built on the Now Platform, our diverse product portfolio addresses critical IT, Employee, and Customer Workflows, providing the enterprise solutions necessary for a thorough digital transformation. Elevate the experiences you offer and unleash the productivity you seek, now enhanced with native mobile functionalities for daily tasks across your organization. This transition to digital workflows is not just beneficial; it is essential for staying competitive in today's fast-paced business landscape. -
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Effortlessly switch between eager and graph modes using TorchScript, while accelerating your journey to production with TorchServe. The torch-distributed backend facilitates scalable distributed training and enhances performance optimization for both research and production environments. A comprehensive suite of tools and libraries enriches the PyTorch ecosystem, supporting development across fields like computer vision and natural language processing. Additionally, PyTorch is compatible with major cloud platforms, simplifying development processes and enabling seamless scaling. You can easily choose your preferences and execute the installation command. The stable version signifies the most recently tested and endorsed iteration of PyTorch, which is typically adequate for a broad range of users. For those seeking the cutting-edge, a preview is offered, featuring the latest nightly builds of version 1.10, although these may not be fully tested or supported. It is crucial to verify that you meet all prerequisites, such as having numpy installed, based on your selected package manager. Anaconda is highly recommended as the package manager of choice, as it effectively installs all necessary dependencies, ensuring a smooth installation experience for users. This comprehensive approach not only enhances productivity but also ensures a robust foundation for development.
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Amazon SageMaker
Amazon
Amazon SageMaker is a comprehensive machine learning platform that integrates powerful tools for model building, training, and deployment in one cohesive environment. It combines data processing, AI model development, and collaboration features, allowing teams to streamline the development of custom AI applications. With SageMaker, users can easily access data stored across Amazon S3 data lakes and Amazon Redshift data warehouses, facilitating faster insights and AI model development. It also supports generative AI use cases, enabling users to develop and scale applications with cutting-edge AI technologies. The platform’s governance and security features ensure that data and models are handled with precision and compliance throughout the entire ML lifecycle. Furthermore, SageMaker provides a unified development studio for real-time collaboration, speeding up data discovery and model deployment. -
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scikit-learn
scikit-learn
FreeScikit-learn offers a user-friendly and effective suite of tools for predictive data analysis, making it an indispensable resource for those in the field. This powerful, open-source machine learning library is built for the Python programming language and aims to simplify the process of data analysis and modeling. Drawing from established scientific libraries like NumPy, SciPy, and Matplotlib, Scikit-learn presents a diverse array of both supervised and unsupervised learning algorithms, positioning itself as a crucial asset for data scientists, machine learning developers, and researchers alike. Its structure is designed to be both consistent and adaptable, allowing users to mix and match different components to meet their unique requirements. This modularity empowers users to create intricate workflows, streamline repetitive processes, and effectively incorporate Scikit-learn into expansive machine learning projects. Furthermore, the library prioritizes interoperability, ensuring seamless compatibility with other Python libraries, which greatly enhances data processing capabilities and overall efficiency. As a result, Scikit-learn stands out as a go-to toolkit for anyone looking to delve into the world of machine learning. -
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Azure Machine Learning
Microsoft
Streamline the entire machine learning lifecycle from start to finish. Equip developers and data scientists with an extensive array of efficient tools for swiftly building, training, and deploying machine learning models. Enhance the speed of market readiness and promote collaboration among teams through leading-edge MLOps—akin to DevOps but tailored for machine learning. Drive innovation within a secure, reliable platform that prioritizes responsible AI practices. Cater to users of all expertise levels with options for both code-centric and drag-and-drop interfaces, along with automated machine learning features. Implement comprehensive MLOps functionalities that seamlessly align with existing DevOps workflows, facilitating the management of the entire machine learning lifecycle. Emphasize responsible AI by providing insights into model interpretability and fairness, securing data through differential privacy and confidential computing, and maintaining control over the machine learning lifecycle with audit trails and datasheets. Additionally, ensure exceptional compatibility with top open-source frameworks and programming languages such as MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R, thus broadening accessibility and usability for diverse projects. By fostering an environment that promotes collaboration and innovation, teams can achieve remarkable advancements in their machine learning endeavors. -
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Llama 2
Meta
FreeIntroducing the next iteration of our open-source large language model, this version features model weights along with initial code for the pretrained and fine-tuned Llama language models, which span from 7 billion to 70 billion parameters. The Llama 2 pretrained models have been developed using an impressive 2 trillion tokens and offer double the context length compared to their predecessor, Llama 1. Furthermore, the fine-tuned models have been enhanced through the analysis of over 1 million human annotations. Llama 2 demonstrates superior performance against various other open-source language models across multiple external benchmarks, excelling in areas such as reasoning, coding capabilities, proficiency, and knowledge assessments. For its training, Llama 2 utilized publicly accessible online data sources, while the fine-tuned variant, Llama-2-chat, incorporates publicly available instruction datasets along with the aforementioned extensive human annotations. Our initiative enjoys strong support from a diverse array of global stakeholders who are enthusiastic about our open approach to AI, including companies that have provided valuable early feedback and are eager to collaborate using Llama 2. The excitement surrounding Llama 2 signifies a pivotal shift in how AI can be developed and utilized collectively.
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