List of Ango Hub Integrations

This is a list of platforms and tools that integrate with Ango Hub. This list is updated as of August 2025.

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    Snowflake Reviews & Ratings

    Snowflake

    Snowflake

    Unlock scalable data management for insightful, secure analytics.
    Snowflake is a leading AI Data Cloud platform designed to help organizations harness the full potential of their data by breaking down silos and streamlining data management with unmatched scale and simplicity. The platform’s interoperable storage capability offers near-infinite access to data across multiple clouds and regions, enabling seamless collaboration and analytics. Snowflake’s elastic compute engine ensures top-tier performance for diverse workloads, automatically scaling to meet demand and optimize costs. Cortex AI, Snowflake’s integrated AI service, provides enterprises secure access to industry-leading large language models and conversational AI capabilities to accelerate data-driven decision making. Snowflake’s comprehensive cloud services automate infrastructure management, helping businesses reduce operational complexity and improve reliability. Snowgrid extends data and app connectivity globally across regions and clouds with consistent security and governance. The Horizon Catalog is a powerful governance tool that ensures compliance, privacy, and controlled access to data assets. Snowflake Marketplace facilitates easy discovery and collaboration by connecting customers to vital data and applications within the AI Data Cloud ecosystem. Trusted by more than 11,000 customers globally, including leading brands across healthcare, finance, retail, and media, Snowflake drives innovation and competitive advantage. Their extensive developer resources, training, and community support empower organizations to build, deploy, and scale AI and data applications securely and efficiently.
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    Azure Blob Storage Reviews & Ratings

    Azure Blob Storage

    Microsoft

    "Empower your cloud strategy with scalable, secure storage."
    Azure Blob Storage offers a highly scalable and secure solution for object storage, specifically designed to meet the demands of cloud-native applications, data lakes, archives, high-performance computing, and machine learning projects. It allows users to create data lakes that align with their analytical needs while providing strong storage options for the development of responsive cloud-native and mobile applications. With its tiered storage capabilities, organizations can efficiently manage costs associated with long-term data storage while retaining the agility to scale resources for intensive high-performance computing and machine learning tasks. Built to fulfill the requirements of security, scalability, and availability, Blob storage is an essential asset for developers working on mobile, web, and cloud-native applications. Moreover, it significantly contributes to serverless architectures, particularly those that leverage Azure Functions. Supporting popular development frameworks such as Java, .NET, Python, and Node.js, Blob storage is distinguished as the only cloud storage service that offers a premium SSD-based object storage tier, which is optimized for low-latency and interactive applications. This adaptability and wide-ranging functionality make it a crucial resource for enterprises aiming to refine their cloud strategies, ultimately driving innovation and efficiency across various sectors.
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    Google Cloud AI Infrastructure Reviews & Ratings

    Google Cloud AI Infrastructure

    Google

    Unlock AI potential with cost-effective, scalable training solutions.
    Today, companies have a wide array of choices for training their deep learning and machine learning models in a cost-effective manner. AI accelerators are designed to address multiple use cases, offering solutions that vary from budget-friendly inference to comprehensive training options. Initiating the process is made easy with a multitude of services aimed at supporting both development and deployment stages. Custom ASICs known as Tensor Processing Units (TPUs) are crafted specifically to optimize the training and execution of deep neural networks, leading to enhanced performance. With these advanced tools, businesses can create and deploy more sophisticated and accurate models while keeping expenditures low, resulting in quicker processing times and improved scalability. A broad assortment of NVIDIA GPUs is also available, enabling economical inference or boosting training capabilities, whether by scaling vertically or horizontally. Moreover, employing RAPIDS and Spark in conjunction with GPUs allows users to perform deep learning tasks with exceptional efficiency. Google Cloud provides the ability to run GPU workloads, complemented by high-quality storage, networking, and data analytics technologies that elevate overall performance. Additionally, users can take advantage of CPU platforms upon launching a VM instance on Compute Engine, featuring a range of Intel and AMD processors tailored for various computational demands. This holistic strategy not only empowers organizations to tap into the full potential of artificial intelligence but also ensures effective cost management, making it easier for them to stay competitive in the rapidly evolving tech landscape. As a result, companies can confidently navigate their AI journeys while maximizing resources and innovation.
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    Azure Databricks Reviews & Ratings

    Azure Databricks

    Microsoft

    Unlock insights and streamline collaboration with powerful analytics.
    Leverage your data to uncover meaningful insights and develop AI solutions with Azure Databricks, a platform that enables you to set up your Apache Spark™ environment in mere minutes, automatically scale resources, and collaborate on projects through an interactive workspace. Supporting a range of programming languages, including Python, Scala, R, Java, and SQL, Azure Databricks also accommodates popular data science frameworks and libraries such as TensorFlow, PyTorch, and scikit-learn, ensuring versatility in your development process. You benefit from access to the most recent versions of Apache Spark, facilitating seamless integration with open-source libraries and tools. The ability to rapidly deploy clusters allows for development within a fully managed Apache Spark environment, leveraging Azure's expansive global infrastructure for enhanced reliability and availability. Clusters are optimized and configured automatically, providing high performance without the need for constant oversight. Features like autoscaling and auto-termination contribute to a lower total cost of ownership (TCO), making it an advantageous option for enterprises aiming to improve operational efficiency. Furthermore, the platform’s collaborative capabilities empower teams to engage simultaneously, driving innovation and speeding up project completion times. As a result, Azure Databricks not only simplifies the process of data analysis but also enhances teamwork and productivity across the board.
  • 5
    AWS AI Services Reviews & Ratings

    AWS AI Services

    Amazon

    Transform your applications with intelligent, effortless AI integration.
    Amazon Web Services (AWS) provides a suite of pre-configured AI Services designed to bring intelligent functionalities to your applications and workflows. These services easily integrate with existing systems to address common needs, such as personalized recommendations, improving contact center operations, enhancing safety protocols, and increasing customer engagement. By utilizing the same sophisticated deep learning technology that powers Amazon.com and its Machine Learning Services, you can expect consistently high-quality and accurate results from APIs that are continuously updated. One of the most advantageous features of AWS AI Services is that they do not require any prior expertise in machine learning, allowing users to efficiently catalog assets, automate workflows, and gain insights from different forms of media and applications. Furthermore, these services excel at identifying missing product parts, spotting damage in vehicles and buildings, and flagging anomalies, which contributes to rigorous quality assurance. By implementing automated monitoring, you can enhance operational efficiency by uncovering bottlenecks and assessing the quality and safety standards in manufacturing processes. In addition, these services are capable of rapidly extracting essential information from vast amounts of documents, facilitating better data utilization and informed decision-making. Consequently, organizations can optimize their processes and achieve substantial gains in overall productivity and effectiveness. By embracing these advanced technologies, businesses can not only improve current operations but also prepare themselves for future challenges.
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