Find and compare the best Artificial Intelligence software for Microsoft Intelligent Data Platform in 2025
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Use the comparison tool below to compare the top Artificial Intelligence software for Microsoft Intelligent Data Platform on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
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Snowflake is a cloud-native data platform that combines data warehousing, data lakes, and data sharing into a single solution. By offering elastic scalability and automatic scaling, Snowflake enables businesses to handle vast amounts of data while maintaining high performance at low cost. The platform's architecture allows users to separate storage and compute, offering flexibility in managing workloads. Snowflake supports real-time data sharing and integrates seamlessly with other analytics tools, enabling teams to collaborate and gain insights from their data more efficiently. Its secure, multi-cloud architecture makes it a strong choice for enterprises looking to leverage data at scale.
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Azure AI Search
Microsoft
$0.11 per hour 198 RatingsAchieve exceptional response quality through a vector database specifically designed for advanced retrieval augmented generation (RAG) and contemporary search functionalities. Emphasize substantial growth with a robust, enterprise-ready vector database that inherently includes security, compliance, and ethical AI methodologies. Create superior applications utilizing advanced retrieval techniques that are underpinned by years of research and proven customer success. Effortlessly launch your generative AI application with integrated platforms and data sources, including seamless connections to AI models and frameworks. Facilitate the automatic data upload from an extensive array of compatible Azure and third-party sources. Enhance vector data processing with comprehensive features for extraction, chunking, enrichment, and vectorization, all streamlined in a single workflow. Offer support for diverse vector types, hybrid models, multilingual capabilities, and metadata filtering. Go beyond simple vector searches by incorporating keyword match scoring, reranking, geospatial search capabilities, and autocomplete features. This holistic approach ensures that your applications can meet a wide range of user needs and adapt to evolving demands. -
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Azure AI Services
Microsoft
1 RatingCreate state-of-the-art, commercially viable AI solutions using both pre-built and customizable APIs and models. Seamlessly integrate generative AI into your production processes through various studios, SDKs, and APIs. Enhance your competitive position by developing AI applications that leverage foundational models from prominent sources like OpenAI, Meta, and Microsoft. Implement safeguards against misuse with integrated responsible AI practices, top-tier Azure security features, and specialized tools for ethical AI development. Design your own copilot and generative AI solutions utilizing advanced language and vision models. Access the most pertinent information through keyword, vector, and hybrid search methodologies. Continuously oversee text and visual content to identify potentially harmful or inappropriate material. Effortlessly translate documents and text in real time, supporting over 100 different languages while ensuring accessibility for diverse audiences. This comprehensive toolkit empowers developers to innovate while prioritizing safety and efficiency in AI deployment. -
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Microsoft Purview
Microsoft
$0.342Microsoft Purview serves as a comprehensive data governance platform that facilitates the management and oversight of your data across on-premises, multicloud, and software-as-a-service (SaaS) environments. With its capabilities in automated data discovery, sensitive data classification, and complete data lineage tracking, you can effortlessly develop a thorough and current representation of your data ecosystem. This empowers data users to access reliable and valuable data easily. The service provides automated identification of data lineage and classification across various sources, ensuring a cohesive view of your data assets and their interconnections for enhanced governance. Through semantic search, users can discover data using both business and technical terminology, providing insights into the location and flow of sensitive information within a hybrid data environment. By leveraging the Purview Data Map, you can lay the groundwork for effective data utilization and governance, while also automating and managing metadata from diverse sources. Additionally, it supports the classification of data using both predefined and custom classifiers, along with Microsoft Information Protection sensitivity labels, ensuring that your data governance framework is robust and adaptable. This combination of features positions Microsoft Purview as an essential tool for organizations seeking to optimize their data management strategies. -
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Microsoft Fabric
Microsoft
$156.334/month/ 2CU Connecting every data source with analytics services on a single AI-powered platform will transform how people access, manage, and act on data and insights. All your data. All your teams. All your teams in one place. Create an open, lake-centric hub to help data engineers connect data from various sources and curate it. This will eliminate sprawl and create custom views for all. Accelerate analysis through the development of AI models without moving data. This reduces the time needed by data scientists to deliver value. Microsoft Teams, Microsoft Excel, and Microsoft Teams are all great tools to help your team innovate faster. Connect people and data responsibly with an open, scalable solution. This solution gives data stewards more control, thanks to its built-in security, compliance, and governance. -
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Azure OpenAI Service
Microsoft
$0.0004 per 1000 tokensUtilize sophisticated coding and language models across a diverse range of applications. Harness the power of expansive generative AI models that possess an intricate grasp of both language and code, paving the way for enhanced reasoning and comprehension skills essential for developing innovative applications. These advanced models can be applied to multiple scenarios, including writing support, automatic code creation, and data reasoning. Moreover, ensure responsible AI practices by implementing measures to detect and mitigate potential misuse, all while benefiting from enterprise-level security features offered by Azure. With access to generative models pretrained on vast datasets comprising trillions of words, you can explore new possibilities in language processing, code analysis, reasoning, inferencing, and comprehension. Further personalize these generative models by using labeled datasets tailored to your unique needs through an easy-to-use REST API. Additionally, you can optimize your model's performance by fine-tuning hyperparameters for improved output accuracy. The few-shot learning functionality allows you to provide sample inputs to the API, resulting in more pertinent and context-aware outcomes. This flexibility enhances your ability to meet specific application demands effectively. -
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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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Azure AI Foundry
Microsoft
Azure AI Foundry serves as a comprehensive application platform tailored for organizations navigating the AI landscape. By connecting advanced AI technologies with real-world business needs, Azure AI Foundry enables companies to fully leverage AI capabilities in a streamlined manner. This platform is specifically crafted to empower every member of an organization—ranging from developers and AI engineers to IT specialists—allowing them to easily customize, host, execute, and oversee AI solutions. Through this cohesive strategy, the development and management processes are significantly streamlined, allowing all participants to concentrate on fostering innovation and realizing their strategic objectives effectively. In doing so, Azure AI Foundry not only enhances individual productivity but also promotes collaborative efforts across various teams. -
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Microsoft Azure Responsible AI
Microsoft
Confidently advance the future of safe and ethical AI applications within your organization. Utilize cutting-edge technologies and established best practices to effectively scale AI while managing risks, enhancing accuracy, safeguarding privacy, ensuring transparency, and streamlining compliance efforts. Equip cross-functional teams with the necessary resources to create the next wave of AI applications in a secure manner, leveraging integrated tools and templates designed to incorporate responsible AI into open source, machine learning operations, and generative AI processes. Proactively identify and address potential misuse through robust responsible AI measures, top-tier Azure security, and specialized AI tools. Monitor both text and images to swiftly recognize and filter out offensive or inappropriate content. Accelerate the deployment of machine learning models and foster collaboration through prompt flow, ultimately achieving a faster return on investment. Build innovative generative AI applications and tailor-made copilots all within a single, cohesive platform, ensuring efficiency and effectiveness in your AI initiatives. Through these strategies, you can create a safer AI landscape that not only meets regulatory requirements but also builds trust with users and stakeholders alike. -
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Azure AI Content Understanding
Microsoft
Azure AI Content Understanding empowers organizations to convert unstructured multimodal data into actionable insights. By extracting valuable information from various input formats including text, audio, images, and video, businesses can unlock essential insights. Employing advanced AI techniques like schema extraction and grounding, it ensures the generation of accurate, high-quality data suitable for further applications. This technology simplifies the integration of diverse data types into a cohesive workflow, resulting in reduced costs and an expedited path to value realization. For instance, businesses and call center operators can leverage insights from call recordings to monitor crucial KPIs, improve product experiences, and respond to customer inquiries more efficiently and accurately. Furthermore, by ingesting a wide array of data types such as documents, images, audio, or video, organizations can utilize various AI models offered in Azure AI to convert raw input into structured outputs that facilitate easier processing and analysis in subsequent applications. Such capabilities ultimately enhance decision-making processes across various sectors.
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