We compared Microsoft Azure Machine Learning Studio and Azure OpenAI based on our user's reviews in several parameters.
Microsoft Azure Machine Learning Studio offers a user-friendly interface, excellent support, and flexible pricing options. Users have highlighted the need for better documentation and collaboration features. Azure OpenAI, on the other hand, focuses on seamless integration, scalable resources, and robust machine learning capabilities. Users appreciate its affordable pricing, extensive support, and positive ROI. Areas for improvement include specific functions and enhancements.
Features: Microsoft Azure Machine Learning Studio offers a user-friendly interface, a wide range of tools and algorithms, seamless integration with other Azure services, reliable and scalable performance, and excellent support and documentation. In comparison, Azure OpenAI focuses on seamless integration with other Azure services, flexibility in resource scaling, robust machine learning capabilities, and extensive documentation and support.
Pricing and ROI: Azure Machine Learning Studio offers flexible pricing options with reasonable setup costs, according to user feedback. On the other hand, Azure OpenAI is positively regarded for its affordable pricing and minimal setup cost. Users find it cost-efficient and note the smooth setup process. Azure OpenAI also provides adaptable licensing options., The ROI of Microsoft Azure Machine Learning Studio includes cost savings, improved efficiency, and reliable predictions. Azure OpenAI offers increased efficiency, cost reduction, and valuable insights for better decision-making.
Room for Improvement: Microsoft Azure Machine Learning Studio: Users have identified areas for improvement, including enhancing the user interface, better documentation and guidance, improved collaboration features, and seamless integration with other tools. Azure OpenAI: Users have provided feedback on enhancing Azure OpenAI, including concerns regarding certain functions and suggested improvements.
Deployment and customer support: The user reviews for Microsoft Azure Machine Learning Studio indicate some variation in the durations for deployment, setup, and implementation phases, suggesting that these processes may occur at different times. In contrast, the reviews for Azure OpenAI suggest that deployment and setup are considered to be the same period and should not be evaluated separately., Microsoft Azure Machine Learning Studio's customer service is praised for being prompt, knowledgeable, and efficient. On the other hand, Azure OpenAI's customer service is regarded as highly appreciated, efficient, and reliable, ensuring a smooth user experience.
The summary above is based on 35 interviews we conducted recently with Microsoft Azure Machine Learning Studio and Azure OpenAI users. To access the review's full transcripts, download our report.
"The most valuable feature of Azure OpenAI stems from the GPT-3.5 models it provides to its users."
"Our clients are interested in building knowledge bases, particularly in child welfare. In this domain, we focus on supporting caseworkers by compiling and organizing relevant information. This information is then stored in a database using a query. The database generates summaries and reminders for specific actions and even facilitates sending emails to parents or other relevant parties. The system's complexity is tailored to the specific needs of child welfare cases. Additionally, we're exploring opportunities to assist a healthcare organization. Specifically, we're working on streamlining the process of filling out forms required for insurance claims. This effort aims to ensure that hospitals can receive funding or payment for the care they provide."
"My goal was to create an experience where project managers don't have to read through entire documents. Instead, they can ask a question and receive relevant point analysis. This analysis identifies the document and specific section where the information resides. Previously, users had to rely on these document references. Now, Azure OpenAI enhances the experience by providing the answer directly in the user's own language, relevant to their context."
"It's very powerful. It allows users to query our documents using natural language and receive answers in the same way. This makes our product information much more accessible than traditional keyword-based search."
"The most crucial aspect is the conversational capability, where you can simply ask questions, and it provides answers based on your content and documents, particularly tailored to your specific environment."
"OpenAI integrates seamlessly with the broader Microsoft Azure ecosystem, and that provides synergies with the other solutions. This integration makes it much easier to build solutions."
"The product's initial setup phase was pretty easy."
"The high precision of information extraction is the most valuable feature."
"It has helped in reducing the time involved for coding using R and/or Python."
"The most valuable feature is its compatibility with Tensorflow."
"Split dataset, variety of algorithms, visualizing the data, and drag and drop capability are the features I appreciate most."
"Microsoft Azure Machine Learning Studio is easy to use and deploy."
"Their support is helpful."
"The product's standout feature is a robust multi-file network with limited availability."
"The most valuable feature is data normalization."
"The initial setup is very simple and straightforward."
"There are no available updates of information that are currently provided."
"Our customers are worried about data management, ethical, and security issues."
"We encountered challenges related to question understanding."
"The fine-tuning of models with the use of Azure OpenAI is an area with certain shortcomings currently, and it can be considered for improvement in the future."
"There are certain shortcomings with the product's scalability and support team where improvements are required."
"The product features themselves are fine. However, with Microsoft scaling the service so much, the support structure needs to keep pace. When solving complex issues, the process of interacting with Microsoft can be quite time-consuming."
"The product must improve its dashboards."
"Sometimes, the responses are repetitive."
"The solution's initial setup process is complicated."
"One area where Azure Machine Learning Studio could improve is its user interface structure."
"In terms of improvement, I'd like to have more ability to construct and understand the detailed impact of the variables on the model. Their algorithms are very powerful and they explain overall the net contribution of each of the variables to the solution. In terms of being able to say to people "If you did this, you'll get this much more improvement" it wasn't great."
"The data preparation capabilities need to be improved."
"The solution should be more customizable. There should be more algorithms."
"Enable creating ensemble models easier, adding more machine learning algorithms."
"Integration with social media would be a valuable enhancement."
"The regulatory requirements of the product need improvement."
More Microsoft Azure Machine Learning Studio Pricing and Cost Advice →
Azure OpenAI is ranked 2nd in AI Development Platforms with 17 reviews while Microsoft Azure Machine Learning Studio is ranked 1st in AI Development Platforms with 49 reviews. Azure OpenAI is rated 8.0, while Microsoft Azure Machine Learning Studio is rated 7.6. The top reviewer of Azure OpenAI writes "Created a chatbot powered by OpenAI to answer HR, travel, and expense-related questions". On the other hand, the top reviewer of Microsoft Azure Machine Learning Studio writes "Good support for Azure services in pipelines, but deploying outside of Azure is difficult". Azure OpenAI is most compared with Google Vertex AI, Amazon SageMaker, Hugging Face, Google Cloud AI Platform and IBM Watson Studio, whereas Microsoft Azure Machine Learning Studio is most compared with Databricks, Google Vertex AI, TensorFlow, Google Cloud AI Platform and Dataiku Data Science Studio. See our Azure OpenAI vs. Microsoft Azure Machine Learning Studio report.
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We monitor all AI Development Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.