Google Cloud AutoML Integrations

Google Cloud is an online service that lets you create everything from simple websites to complex apps for businesses of any size. Customers who are new to the system will receive $300 in credits for testing, deploying, and running workloads. Customers can use up to 25+ products free of charge. Use Google's core data analytics and machine learning. All enterprises can use it. It is secure and fully featured. Use big data to build better products and find answers faster. You can grow from prototypes to production and even to planet-scale without worrying about reliability, capacity or performance. Virtual machines with proven performance/price advantages, to a fully-managed app development platform. High performance, scalable, resilient object storage and databases. Google's private fibre network offers the latest software-defined networking solutions. Fully managed data warehousing and data exploration, Hadoop/Spark and messaging.

Evoltsoft’s EV Charging Management Platform (EVMP) is a cutting edge solution designed to streamline the operation of electric vehicles charging stations. Our platform is designed to provide a seamless experience, both for operators and users. It focuses on user-friendly features and functionality. Key features include real time monitoring of charging stations occupancy, intuitive mobile applications for users, IoT parking sensors, license plates recognition, online booking and reservation tools, cashless payments methods, and customizable charging infrastructures for electric vehicles (EVs). The platform offers more than just basic functionality. It also provides scalability and growth options for businesses that have electric vehicle fleets. Advanced features include usage reporting and tracking, billing and payments integration, integration with Fleet Management Software, remote monitoring and control, and integration with Energy Management Systems.

At Axon Ivy, we tackle one of the most significant challenges that organizations encounter today—optimizing inefficient business processes. Business leaders must strategize and implement successful digital transformations to achieve their goals, while department heads require quick and adaptable support to enhance their operations. Additionally, IT managers seek a versatile tool that allows them to coordinate comprehensive business processes seamlessly. In the rapidly changing business landscape, speed and adaptability are crucial to meet ongoing demands and shifts. Our award-winning platform, recognized by Forrester and Gartner, significantly improves the way our clients and partners operate across a variety of industries. Discover how simple and efficient it can be to digitize, orchestrate, and automate your business workflows. Axon Ivy serves as a digital process automation (DPA) platform utilized by more than 500 clients globally, addressing all facets of end-to-end automation. Not only does the platform accommodate no-code and low-code development, but it also supports full-code development, ensuring flexibility for users with various technical expertise. This commitment to versatility empowers organizations to tailor their process automation strategies to best fit their unique needs.

Leverage advanced machine learning techniques for thorough text analysis that can extract, interpret, and securely store textual data. With AutoML, you can create top-tier custom machine learning models effortlessly, without writing any code. Implement natural language understanding through the Natural Language API to enhance your applications. Utilize entity analysis to pinpoint and categorize various fields in documents, such as emails, chats, and social media interactions, followed by sentiment analysis to gauge customer feedback and derive actionable insights for product improvements and user experience. The Natural Language API, combined with speech-to-text capabilities, can also provide valuable insights from audio sources. Additionally, the Vision API enhances your capabilities with optical character recognition (OCR) for digitizing scanned documents. The Translation API further enables sentiment understanding across diverse languages. With custom entity extraction, you can identify specialized entities within your documents that may not be recognized by standard models, saving both time and resources on manual processing. Ultimately, you can train your own high-quality machine learning models to effectively classify, extract, and assess sentiment, making your analysis more targeted and efficient. This comprehensive approach ensures a robust understanding of textual and audio data, empowering businesses with deeper insights.

Dataiku serves as a sophisticated platform for data science and machine learning, aimed at facilitating teams in the construction, deployment, and management of AI and analytics projects on a large scale. It enables a diverse range of users, including data scientists and business analysts, to work together in developing data pipelines, crafting machine learning models, and preparing data through various visual and coding interfaces. Supporting the complete AI lifecycle, Dataiku provides essential tools for data preparation, model training, deployment, and ongoing monitoring of projects. Additionally, the platform incorporates integrations that enhance its capabilities, such as generative AI, thereby allowing organizations to innovate and implement AI solutions across various sectors. This adaptability positions Dataiku as a valuable asset for teams looking to harness the power of AI effectively.

Modern, Automated & Shared Employee & Group Health Benefit Platform ASPIRE HEALTH by ARTIVATIC is proud to provide a MODERN & AUTOMATED PLATFORM FOR EMPLOYEE & GROUP HEALTH BENEFITS. ASPIRE HEALTH is aimed to drive better outcome, efficiency, standardization, simplification, and connecting as Shared Platform for brokers, carriers, TPAs, 3rd Parties and customers (SMEs, Businesses etc.) on one Unified Platform.

Leverage the most extensively utilized observability platform, founded on the reliable Elastic Stack (commonly referred to as the ELK Stack), to integrate disparate data sources, providing cohesive visibility and actionable insights. To truly monitor and extract insights from your distributed systems, it is essential to consolidate all your observability data within a single framework. Eliminate data silos by merging application, infrastructure, and user information into a holistic solution that facilitates comprehensive observability and alerting. By integrating limitless telemetry data collection with search-driven problem-solving capabilities, you can achieve superior operational and business outcomes. Unify your data silos by assimilating all telemetry data, including metrics, logs, and traces, from any source into a platform that is open, extensible, and scalable. Enhance the speed of problem resolution through automatic anomaly detection that leverages machine learning and sophisticated data analytics, ensuring you stay ahead in today's fast-paced environment. This integrated approach not only streamlines processes but also empowers teams to make informed decisions swiftly.

Luminoth is an open-source framework designed for computer vision applications, currently focusing on object detection but with aspirations to expand its capabilities. As it is in the alpha stage, users should be aware that both internal and external interfaces, including the command line, are subject to change as development progresses. For those interested in utilizing GPU support, it is recommended to install the GPU variant of TensorFlow via pip with the command pip install tensorflow-gpu; alternatively, users can opt for the CPU version by executing pip install tensorflow. Additionally, Luminoth offers the convenience of installing TensorFlow directly by using either pip install luminoth[tf] or pip install luminoth[tf-gpu], depending on the desired TensorFlow version. Overall, Luminoth represents a promising tool in the evolving landscape of computer vision technology.

The Media Translation API provides instantaneous translation of speech for your content and applications, directly utilizing your audio files. By harnessing the power of Google’s advanced machine learning technologies, this API ensures superior accuracy and seamless integration, while also offering a robust suite of features to optimize your translation outcomes. Enhance the user experience with fast, low-latency streaming translation and easily expand your reach with straightforward internationalization options. Google Cloud’s renowned translation and speech recognition capabilities are a testament to its high quality, stemming from years of expertise in machine learning. By integrating innovative technologies, the Media Translation API delivers top-tier audio translation, combining the capabilities of both the popular Translation API and the speech-to-text API. You can now translate audio data directly, and the Media Translation API significantly boosts the precision of interpretation by refining the integration of models from audio to text. With its state-of-the-art features and reliable performance, this API is poised to transform how you approach audio translation tasks.

Advanced video analysis technology can identify more than 20,000 different objects, locations, and activities within video content. It allows for the extraction of comprehensive metadata across various levels, including the entire video, individual shots, or specific frames. Users have the capability to define custom entity labels through AutoML Video Intelligence, tailoring the tool to their needs. Additionally, it offers the ability to gather insights in near real-time, using streaming video annotation alongside object-based event triggers. This functionality enables the creation of captivating customer experiences through highlight reels and personalized recommendations. Furthermore, it supports the recognition of over 20,000 objects, places, and actions in both stored and live video feeds. Users can search their video libraries in a manner similar to document searches, facilitating easier access to specific content. The rich metadata extracted can also serve to index, organize, and filter video assets, ensuring that the most relevant content is highlighted. With these features, organizations can leverage video data more effectively to enhance their operations and engage their audiences.

The Google Cloud Healthcare API is a comprehensive managed service designed to facilitate secure and scalable data exchange among healthcare applications and services. It accommodates widely recognized protocols and formats like DICOM, FHIR, and HL7v2, which supports the ingestion, storage, and analysis of healthcare-related data in the Google Cloud ecosystem. Furthermore, by connecting with sophisticated analytics and machine learning platforms such as BigQuery, AutoML, and Vertex AI, this API enables healthcare organizations to extract valuable insights and foster innovation in both patient care and operational processes. This capability ultimately enhances decision-making and improves overall healthcare delivery.

ML.NET is a versatile, open-source machine learning framework that is free to use and compatible across platforms, enabling .NET developers to create tailored machine learning models using C# or F# while remaining within the .NET environment. This framework encompasses a wide range of machine learning tasks such as classification, regression, clustering, anomaly detection, and recommendation systems. Additionally, ML.NET seamlessly integrates with other renowned machine learning frameworks like TensorFlow and ONNX, which broadens the possibilities for tasks like image classification and object detection. It comes equipped with user-friendly tools such as Model Builder and the ML.NET CLI, leveraging Automated Machine Learning (AutoML) to streamline the process of developing, training, and deploying effective models. These innovative tools automatically analyze various algorithms and parameters to identify the most efficient model for specific use cases. Moreover, ML.NET empowers developers to harness the power of machine learning without requiring extensive expertise in the field.

Beats serves as a free and accessible platform designed specifically for single-purpose data shippers that transport data from numerous machines and systems to Logstash or Elasticsearch. These open-source data shippers are installed as agents on your servers, enabling the seamless transfer of operational data to Elasticsearch. Elastic offers Beats to facilitate the collection of data and event logs efficiently. Data can be directed to Elasticsearch or routed through Logstash, allowing for additional processing and enhancement before visualization in Kibana. If you're eager to start monitoring infrastructure metrics and centralizing log analytics swiftly, the Metrics app and Logs app in Kibana are excellent resources to explore. For comprehensive guidance, refer to Analyze metrics and Monitor logs. Filebeat simplifies the process of collecting data from various sources, including security devices, cloud environments, containers, and hosts, by providing a lightweight solution to forward and centralize logs and files. This flexibility ensures that you can maintain an organized and efficient data pipeline regardless of the complexity of your infrastructure.

A customer intelligence platform designed to aid brands in examining and forecasting user behavior across various channels is essential for modern marketing strategies. This platform enables swift and precise data analysis, allowing businesses to uncover behavioral patterns and trends for informed decision-making, leveraging the capabilities of AI and machine learning. B2Metric seamlessly connects with a wide array of data sources, including commonly used databases, to facilitate comprehensive insights. By predicting customer churn, brands can enhance their retention strategies and implement timely preventive measures. Additionally, customers can be categorized into specific segments based on their behaviors, attributes, and preferences, thus allowing for more targeted marketing initiatives. The refinement of marketing strategies through data-driven insights boosts performance, enhances targeting precision, personalizes customer interactions, and optimizes budget allocation. Furthermore, creating tailored marketing efforts and optimizing touchpoints leads to distinctive customer experiences. With AI-driven marketing analytics, businesses can effectively reduce user churn while fostering growth. By identifying customers at risk of leaving, companies can devise proactive retention strategies utilizing sophisticated machine learning algorithms, ultimately ensuring sustained engagement and loyalty. This comprehensive approach to customer intelligence empowers brands to thrive in an increasingly competitive landscape.

AWS Marketplace serves as a carefully organized digital platform that allows users to explore, buy, implement, and oversee third-party software, data products, and services seamlessly within the AWS environment. This marketplace offers a vast array of options spanning various categories, including security, machine learning, business applications, and DevOps tools. By featuring adaptable pricing structures like pay-as-you-go, annual subscriptions, and free trials, AWS Marketplace makes it easier for customers to manage procurement and billing by consolidating expenses into a single AWS invoice. Additionally, it facilitates quick deployment of pre-configured software that can be easily launched on AWS infrastructure. This efficient model not only empowers businesses to spur innovation and reduce time-to-market but also enhances their ability to control software utilization and costs effectively. Ultimately, AWS Marketplace stands as an essential tool for organizations looking to optimize their software management and procurement processes.

IntelliPay is a comprehensive payment processing and recurring billing solution designed for businesses operating on SaaS, subscription, and service models. Our platform supports both traditional fee structures and no-cost models where cardholders cover the processing fees. We seamlessly integrate with top payment gateways and provide a variety of payment options, including Online Payments, Virtual, On-Demand, Recurring Installments, EMV, and Custom Portals. Historically, businesses that accepted payments would typically bear the costs associated with processing fees, but our innovative technology and recent regulatory changes now empower you with choices. You can either continue to absorb these fees or transfer them to your customers, allowing you to retain a larger portion of your revenue. We offer diverse options that can reduce or eliminate costs for organizations across various industries. To explore our solutions tailored to specific sectors, please refer to the list provided below. Our versatile enterprise payment platform is designed to be highly scalable, easily integrable, and to enhance revenue growth significantly. Additionally, we ensure that patients have access to every available payment method without adding extra strain on your staff.

Amazon SageMaker equips users with an extensive suite of tools and libraries essential for developing machine learning models, emphasizing an iterative approach to experimenting with various algorithms and assessing their performance to identify the optimal solution for specific needs. Within SageMaker, you can select from a diverse range of algorithms, including more than 15 that are specifically designed and enhanced for the platform, as well as access over 150 pre-existing models from well-known model repositories with just a few clicks. Additionally, SageMaker includes a wide array of model-building resources, such as Amazon SageMaker Studio Notebooks and RStudio, which allow you to execute machine learning models on a smaller scale to evaluate outcomes and generate performance reports, facilitating the creation of high-quality prototypes. The integration of Amazon SageMaker Studio Notebooks accelerates the model development process and fosters collaboration among team members. These notebooks offer one-click access to Jupyter environments, enabling you to begin working almost immediately, and they also feature functionality for easy sharing of your work with others. Furthermore, the platform's overall design encourages continuous improvement and innovation in machine learning projects.