Azure Machine Learning Integrations

Approximately 25 million engineers are employed across a wide variety of specific roles. As companies increasingly transform into software-centric organizations, engineers are leveraging New Relic to obtain real-time insights and analyze performance trends of their applications. This capability enables them to enhance their resilience and deliver outstanding customer experiences. New Relic stands out as the sole platform that provides a comprehensive all-in-one solution for these needs. It supplies users with a secure cloud environment for monitoring all metrics and events, robust full-stack analytics tools, and clear pricing based on actual usage. Furthermore, New Relic has cultivated the largest open-source ecosystem in the industry, simplifying the adoption of observability practices for engineers and empowering them to innovate more effectively. This combination of features positions New Relic as an invaluable resource for engineers navigating the evolving landscape of software development.

Microsoft Azure is a dynamic cloud computing platform designed to streamline the development, testing, and management of applications with speed and security. By leveraging Azure, you can creatively turn your ideas into effective solutions, taking advantage of more than 100 services that support building, deploying, and managing applications across various environments such as the cloud, on-premises, or at the edge, all while using your preferred tools and frameworks. The ongoing innovations from Microsoft ensure that your current development requirements are met while also setting the stage for your future product goals. With a strong commitment to open-source values and support for all programming languages and frameworks, Azure grants you the flexibility to create and deploy in a manner that best fits your needs. Whether your infrastructure is on-premises, cloud-based, or edge-focused, Azure is equipped to evolve alongside your existing setup. It also provides specialized services for hybrid cloud frameworks, allowing for smooth integration and effective management. Security is a key pillar of Azure, underpinned by a skilled team and proactive compliance strategies that are trusted by a wide range of organizations, including enterprises, governments, and startups. With Azure, you gain a dependable cloud solution, supported by outstanding performance metrics that confirm its reliability. Furthermore, this platform not only addresses your immediate requirements but also prepares you for the future's dynamic challenges while fostering a culture of innovation and growth.

The NVIDIA Triton™ inference server delivers powerful and scalable AI solutions tailored for production settings. As an open-source software tool, it streamlines AI inference, enabling teams to deploy trained models from a variety of frameworks including TensorFlow, NVIDIA TensorRT®, PyTorch, ONNX, XGBoost, and Python across diverse infrastructures utilizing GPUs or CPUs, whether in cloud environments, data centers, or edge locations. Triton boosts throughput and optimizes resource usage by allowing concurrent model execution on GPUs while also supporting inference across both x86 and ARM architectures. It is packed with sophisticated features such as dynamic batching, model analysis, ensemble modeling, and the ability to handle audio streaming. Moreover, Triton is built for seamless integration with Kubernetes, which aids in orchestration and scaling, and it offers Prometheus metrics for efficient monitoring, alongside capabilities for live model updates. This software is compatible with all leading public cloud machine learning platforms and managed Kubernetes services, making it a vital resource for standardizing model deployment in production environments. By adopting Triton, developers can achieve enhanced performance in inference while simplifying the entire deployment workflow, ultimately accelerating the path from model development to practical application.

Transform what once required years into mere minutes with our user-friendly, flexible, scalable, and secure machine learning monitoring solution. You will discover all the essential tools needed to implement, maintain, and improve machine learning within a production setting. Superwise features an open platform that effortlessly integrates with any existing machine learning frameworks and works harmoniously with your favorite communication tools. Should you wish to delve deeper, Superwise is built on an API-first design, allowing every capability to be accessed through our APIs, which are compatible with your preferred cloud platform. With Superwise, you gain comprehensive self-service capabilities for your machine learning monitoring needs. Metrics and policies can be configured through our APIs and SDK, or you can select from a range of monitoring templates that let you establish sensitivity levels, conditions, and alert channels tailored to your requirements. Experience the advantages of Superwise firsthand, or don’t hesitate to contact us for additional details. Effortlessly generate alerts utilizing Superwise’s policy templates and monitoring builder, where you can choose from various pre-set monitors that tackle challenges such as data drift and fairness, or customize policies to incorporate your unique expertise and insights. This adaptability and user-friendliness provided by Superwise enables users to proficiently oversee their machine learning models, ensuring optimal performance and reliability. With the right tools at your fingertips, managing machine learning has never been more efficient or intuitive.

Kedro is an essential framework that promotes clean practices in the field of data science. By incorporating software engineering principles, it significantly boosts the productivity of machine-learning projects. A Kedro project offers a well-organized framework for handling complex data workflows and machine-learning pipelines. This structured approach enables practitioners to reduce the time spent on tedious implementation duties, allowing them to focus more on tackling innovative challenges. Furthermore, Kedro standardizes the development of data science code, which enhances collaboration and problem-solving among team members. The transition from development to production is seamless, as exploratory code can be transformed into reproducible, maintainable, and modular experiments with ease. In addition, Kedro provides a suite of lightweight data connectors that streamline the processes of saving and loading data across different file formats and storage solutions, thus making data management more adaptable and user-friendly. Ultimately, this framework not only empowers data scientists to work more efficiently but also instills greater confidence in the quality and reliability of their projects, ensuring they are well-prepared for future challenges in the data landscape.

Facilitate the creation, storage, protection, inspection, copying, and management of container images and artifacts through a fully managed, geo-redundant OCI distribution instance. Effortlessly connect diverse environments, including Azure Kubernetes Service and Azure Red Hat OpenShift, along with various Azure services such as App Service, Machine Learning, and Batch. Thanks to the geo-replication feature, users can effectively manage a unified registry that operates across several regions. The OCI artifact repository supports the inclusion of helm charts, singularity compatibility, and new formats that adhere to OCI standards. Enhancing operational efficiency, automated workflows for building and updating containers—including base image revisions and scheduled tasks—are implemented. Comprehensive security measures are put in place, incorporating Azure Active Directory (Azure AD) authentication, role-based access control, Docker content trust, and integration with virtual networks. Azure Container Registry Tasks streamline the building, testing, pushing, and deploying of images to Azure, leading to a more efficient workflow. This holistic management strategy not only fosters improved collaboration but also significantly shortens the development lifecycle within cloud ecosystems, ultimately leading to faster project completions and greater innovation.

Data Science Virtual Machines (DSVMs) are customized images of Azure Virtual Machines that are pre-loaded with a diverse set of crucial tools designed for tasks involving data analytics, machine learning, and artificial intelligence training. They provide a consistent environment for teams, enhancing collaboration and sharing while taking full advantage of Azure's robust management capabilities. With a rapid setup time, these VMs offer a completely cloud-based desktop environment oriented towards data science applications, enabling swift and seamless initiation of both in-person classes and online training sessions. Users can engage in analytics operations across all Azure hardware configurations, which allows for both vertical and horizontal scaling to meet varying demands. The pricing model is flexible, as you are only charged for the resources that you actually use, making it a budget-friendly option. Moreover, GPU clusters are readily available, pre-configured with deep learning tools to accelerate project development. The VMs also come equipped with examples, templates, and sample notebooks validated by Microsoft, showcasing a spectrum of functionalities that include neural networks using popular frameworks such as PyTorch and TensorFlow, along with data manipulation using R, Python, Julia, and SQL Server. In addition, these resources cater to a broad range of applications, empowering users to embark on sophisticated data science endeavors with minimal setup time and effort involved. This tailored approach significantly reduces barriers for newcomers while promoting innovation and experimentation in the field of data science.

Slingshot serves as a comprehensive digital workspace that integrates the finest elements of conventional office software to enhance team efficiency. This platform uniquely merges data analytics, project management, information management, communication tools, goal-oriented strategy assessment, and additional data analytics features. By facilitating easier information retrieval, Slingshot cultivates a sense of calm and efficiency across teams, departments, clients, and external stakeholders. Utilizing data effectively allows your team to boost productivity and derive actionable insights, which can lead to improved outcomes. When everyone aligns their focus on shared objectives and strategies, success becomes more achievable. Additionally, fostering a culture that promotes ownership, accountability, and transparency within workflows is essential. More organizations are adopting Slingshot to elevate their workplace dynamics, enhance project outcomes, and benefit from an innovative software solution that unlocks their teams' potential. Furthermore, Slingshot seamlessly integrates with your essential business tools, establishing itself as the central hub for your project management needs. As a result, teams can collaborate more efficiently and achieve their goals with greater ease.

The Azure Kinect serves as a sophisticated toolkit for spatial computing, equipped with enhanced computer vision and voice recognition features, cutting-edge AI sensors, and a variety of powerful software development kits that integrate seamlessly with Azure AI Services. As a result, organizations in industries like manufacturing, retail, healthcare, and media are utilizing the Azure Kinect to leverage spatial data and contextual insights, leading to improved safety, increased operational efficiency, superior outcomes, and innovative transformations in the customer experience. This technology enables the analysis and refinement of exercise movements for individuals, creating a smart gym atmosphere that optimizes fitness results or aids in effective virtual rehabilitation programs. Furthermore, it merges real-time depth perception information with AI-driven insights, which can significantly improve patient safety in healthcare environments by providing predictive alerts that can prevent accidents and injuries. The device is equipped with a 1-megapixel depth sensor that offers both wide and narrow field-of-view (FOV) options, allowing users to customize the system based on specific application requirements, thus enhancing its overall effectiveness and utility. With its diverse applications and versatility, the Azure Kinect is not just a tool for today but a foundation for future innovations in various fields.

Deliver outstanding results through a sophisticated vector database tailored for advanced retrieval augmented generation (RAG) and modern search techniques. Focus on substantial expansion with an enterprise-class vector database that incorporates robust security protocols, adherence to compliance guidelines, and ethical AI practices. Elevate your applications by utilizing cutting-edge retrieval strategies backed by thorough research and demonstrated client success stories. Seamlessly initiate your generative AI application with easy integrations across multiple platforms and data sources, accommodating various AI models and frameworks. Enable the automatic import of data from a wide range of Azure services and third-party solutions. Refine the management of vector data with integrated workflows for extraction, chunking, enrichment, and vectorization, ensuring a fluid process. Provide support for multivector functionalities, hybrid methodologies, multilingual capabilities, and metadata filtering options. Move beyond simple vector searching by integrating keyword match scoring, reranking features, geospatial search capabilities, and autocomplete functions, thereby creating a more thorough search experience. This comprehensive system not only boosts retrieval effectiveness but also equips users with enhanced tools to extract deeper insights from their data, fostering a more informed decision-making process. Furthermore, the architecture encourages continual innovation, allowing organizations to stay ahead in an increasingly competitive landscape.

MLflow is a comprehensive open-source platform aimed at managing the entire machine learning lifecycle, which includes experimentation, reproducibility, deployment, and a centralized model registry. This suite consists of four core components that streamline various functions: tracking and analyzing experiments related to code, data, configurations, and results; packaging data science code to maintain consistency across different environments; deploying machine learning models in diverse serving scenarios; and maintaining a centralized repository for storing, annotating, discovering, and managing models. Notably, the MLflow Tracking component offers both an API and a user interface for recording critical elements such as parameters, code versions, metrics, and output files generated during machine learning execution, which facilitates subsequent result visualization. It supports logging and querying experiments through multiple interfaces, including Python, REST, R API, and Java API. In addition, an MLflow Project provides a systematic approach to organizing data science code, ensuring it can be effortlessly reused and reproduced while adhering to established conventions. The Projects component is further enhanced with an API and command-line tools tailored for the efficient execution of these projects. As a whole, MLflow significantly simplifies the management of machine learning workflows, fostering enhanced collaboration and iteration among teams working on their models. This streamlined approach not only boosts productivity but also encourages innovation in machine learning practices.

Azure Percept is a comprehensive and intuitive platform that bolsters the security of edge AI solution development. You can get started on your proof of concept within minutes by leveraging hardware accelerators that are specifically engineered for seamless integration with Azure AI and Azure IoT services. The platform functions directly with Azure Cognitive Services, Azure Machine Learning, and an array of other Azure tools to deliver instantaneous insights for visual and auditory data. This all-in-one edge AI platform incorporates integrated hardware accelerators that connect effortlessly to Azure's AI and IoT services, facilitating a streamlined experience. With access to pre-built AI models and management tools, you can swiftly initiate your proof of concept. Furthermore, robust security features are woven into your edge AI solution, protecting your most crucial and valuable resources. You can also tap into a diverse library of ready-made AI models that provide vision capabilities, such as object detection and shelf analytics, as well as audio functionalities like voice control and anomaly recognition. The platform empowers users to customize AI model training without requiring any coding skills, allowing for deployment options that include both local and cloud environments. This level of flexibility guarantees that users can adapt their AI solutions to meet specific requirements while ensuring top-notch security and operational effectiveness. Ultimately, Azure Percept represents a significant advancement in making edge AI more accessible and secure for organizations of all sizes.

Evvox is a versatile platform specifically crafted for the insurance industry. Our main objective is to help you explore new growth opportunities while improving your business performance. This is accomplished through an innovative combination of advanced analytics, artificial intelligence, machine learning, smart routing, customer segmentation, lifetime value evaluation, and strategies for cross-selling and upselling, all of which are readily accessible for your organization. A key highlight of our data platform is its ability to seamlessly integrate new data into existing models, ensuring that information is presented in the most relevant manner for your specific needs. With 25 years of experience in data ingestion, we have optimized our processes to enhance the speed of new data integration by five to ten times. We supply crucial data models along with external data sources, while you contribute your existing data, enabling us to build a strong foundation for actionable insights together. These insights are then delivered straight to your sales team, equipping them to unlock greater value for customers and pursue new business prospects. By utilizing our platform, you can effectively convert data into a competitive advantage that not only drives growth but also cultivates enduring customer relationships. Ultimately, our commitment to innovation and collaboration ensures that your business remains at the forefront of the industry.

The Wizata Platform empowers the manufacturing sector to embrace digital transformation effectively. It supports the creation of AI solutions that range from initial proof of concept to actionable production recommendations, ensuring comprehensive control loops via artificial intelligence. As a Software as a Service (SaaS) platform, it orchestrates various assets—including machines, sensors, and edge computing—allowing for seamless data collection and analysis. This platform serves as your central hub for management, enabling you to allocate resources and prioritize projects based on the effectiveness of your AI solutions in addressing business challenges and enhancing production efficiency. Furthermore, since 2004, we have been dedicated to establishing best practices in data science specifically tailored for the metallurgic industry. With our expertise, manufacturers can confidently navigate the complexities of digital innovation.

Data is fundamental to all operations within a processing facility, acting as the cornerstone for workflows, strategic planning, and environmental oversight. However, complications often arise from this very data, leading to operator errors, faulty sensors, safety issues, or subpar analytics. APERIO is designed to effectively tackle these problems. The reliability of data is essential for Industry 4.0, supporting advanced applications such as predictive analytics, process optimization, and custom AI solutions. APERIO DataWise, known for its robust reliability, stands out as the leading source of trustworthy data. By automating the quality assurance for your PI data or digital twins in a scalable and continuous manner, organizations can guarantee validated information that enhances asset dependability. This not only enables operators to make well-informed decisions but also helps in identifying risks to operational data, which is crucial for sustaining operational resilience. Additionally, it offers accurate monitoring and reporting of sustainability metrics, thus fostering more responsible and efficient practices. In the current landscape driven by data, harnessing dependable information has transitioned from being a mere advantage to an essential requirement for achieving success. The integration of high-quality data solutions can transform the way organizations approach their operational challenges and sustainability goals.

The era of artificial intelligence is upon us. As regulations evolve and technological advancements accelerate rapidly, it becomes essential to ask how you can maintain the compliance, security, and reliability of your AI systems and those of your partners. Cranium provides valuable insights for cybersecurity professionals and data scientists on the implications of AI for their infrastructures, data, and services. By safeguarding your organization's AI and machine learning frameworks without interrupting your operational processes, you can uphold both compliance and credibility. Additionally, it is crucial to defend your AI models against adversarial attacks while ensuring they can still be trained, tested, and deployed effectively. This proactive approach not only enhances security but also fosters trust among users and stakeholders.

Easily deploy applications in the cloud using your chosen programming languages and frameworks, ensuring seamless business continuity while quickly responding to changes in customer demand through features like high availability and elastic scaling. Benefit from unparalleled security and compliance, bolstered by Azure IP Advantage, and take advantage of Microsoft’s extensive global network of data centers. Customize resources to match your workloads with no unexpected fees, allowing for greater budget predictability. By using MariaDB Community edition in tandem with a fully managed service, developers are freed from the burdens of infrastructure and database management, enabling them to focus on building exceptional applications. Azure Database for MariaDB works flawlessly with popular open-source frameworks and languages, ensuring robust compatibility with Azure web apps. Additionally, it can be integrated with leading content management systems such as WordPress and Drupal, providing a seamless experience tailored to your specific application development needs. With these advanced capabilities, developers can explore new ideas and innovate with greater efficiency, significantly boosting their overall productivity. This enhanced focus on innovation not only streamlines workflows but also helps in delivering superior products to end users.

ModelOp is a leader in providing AI governance solutions that enable companies to safeguard their AI initiatives, including generative AI and Large Language Models (LLMs), while also encouraging innovation. As executives strive for the quick adoption of generative AI technologies, they face numerous hurdles such as financial costs, adherence to regulations, security risks, privacy concerns, ethical questions, and threats to their brand reputation. With various levels of government—global, federal, state, and local—moving swiftly to implement AI regulations and oversight, businesses must take immediate steps to comply with these developing standards intended to reduce risks associated with AI. Collaborating with specialists in AI governance can help organizations stay abreast of market trends, regulatory developments, current events, research, and insights that enable them to navigate the complexities of enterprise AI effectively. ModelOp Center not only enhances organizational security but also builds trust among all involved parties. By improving processes related to reporting, monitoring, and compliance throughout the organization, companies can cultivate a culture centered on responsible AI practices. In a rapidly changing environment, it is crucial for organizations to remain knowledgeable and compliant to achieve long-term success, while also being proactive in addressing any potential challenges that may arise.

We enable organizations to leverage the capabilities of first-party data collaboration while effectively reducing any potential risks involved. By transforming consumer data from a possible liability into a lucrative asset, companies can thrive in an evolving landscape that has surpassed traditional cookie usage. Our method promotes stronger partnerships with additional collaborators, which in turn amplifies value for clients. Additionally, we promote financial inclusion and enhance revenue through pioneering alliances that tap into alternative data resources. Our solution improves the precision of underwriting and increases profitability by integrating these varied data streams. Each participant utilizes our secure desktop application to anonymize, tokenize, and protect all personally identifiable information within their consumer data, ensuring it stays secure in their local setting. This process generates US-patented crypto-IDs for every anonymized consumer profile, facilitating the secure linking of shared consumers across multiple datasets within our neutral Cloud infrastructure. By employing our state-of-the-art technology, we are leading the charge in the next phase of consumer data management and collaboration. This guarantees that businesses can prosper in a data-centric future while adhering to the utmost standards of privacy and security, ultimately fostering greater trust and transparency in the marketplace.

The Microsoft Intelligent Data Platform functions as an integrated solution for data and AI, enabling organizations to swiftly adapt, integrate intelligence into their applications, and extract valuable predictive insights. By aligning databases, analytics, and governance, this platform frees businesses to concentrate on value creation rather than the complexities of data management. It facilitates seamless data integration and delivers real-time business intelligence, fostering effective decision-making and propelling innovation forward. By breaking down data silos, organizations can access immediate insights while upholding the vital data governance required for secure operations. Furthermore, the platform promotes innovation and enhances productivity through automation and AI, while also improving agility by predicting changes and refining decision-making processes. Security remains a paramount concern, as the platform offers robust safeguards throughout the data lifecycle, protecting both hybrid and multi-cloud environments. This holistic approach not only simplifies data management but also nurtures a culture within organizations that values informed and proactive responses to challenges. As organizations leverage these capabilities, they position themselves to thrive in an increasingly data-driven world.

BotCore serves as an accelerator enabling businesses to develop tailored conversational bots driven by artificial intelligence. This platform is adaptable, allowing integration with various AI services and offering scalability for future enhancements. Additionally, it can be seamlessly implemented within Microsoft Azure, leveraging numerous features offered by the cloud platform. Organizations can thus benefit from both customization and robust infrastructure as they expand their conversational capabilities.

The Azure Marketplace operates as a vast digital platform, offering users access to a multitude of certified software applications, services, and solutions from Microsoft along with numerous third-party vendors. This marketplace enables businesses to efficiently find, obtain, and deploy software directly within the Azure cloud ecosystem. It showcases a wide range of offerings, including virtual machine images, frameworks for AI and machine learning, developer tools, security solutions, and niche applications designed for specific sectors. With a variety of pricing options such as pay-as-you-go, free trials, and subscription-based plans, the Azure Marketplace streamlines the purchasing process while allowing for consolidated billing through a unified Azure invoice. Additionally, it guarantees seamless integration with Azure services, which empowers organizations to strengthen their cloud infrastructure, improve operational efficiency, and accelerate their journeys toward digital transformation. In essence, the Azure Marketplace is crucial for enterprises aiming to stay ahead in a rapidly changing technological environment while fostering innovation and adaptability. This platform is not just a marketplace; it is a gateway to unlocking the potential of cloud capabilities for businesses worldwide.