We performed a comparison between Azure OpenAI and DataRobot based on real PeerSpot user reviews.
Find out in this report how the two AI Development Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."We have many use cases for the solution, such as digitalizing records, a chatbot looking at records, and being able to use generative AI on them."
"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."
"Two aspects I appreciate are the turnaround time and ease of use. As it's a managed service, the quick turnaround is beneficial, and the simple interface makes it easy to work with. Performance and scalability are also strong points since you can scale as needed."
"The most valuable feature is the ALM."
"The product's initial setup phase was pretty easy."
"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."
"The high precision of information extraction is the most valuable feature."
"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."
"DataRobot can be easy to use."
"It's easy to do MLOps operations. It's a lot easier to manage jobs and see the logs if there's any drift in a model."
"We especially like the initial part of feature engineering, because feature engineering is included in most engines, but DataRobot has an excellent way of picking up the right features."
"Deployment was slightly complex for me to understand."
"Azure OpenAI is not an optimized tool yet, making it one of its shortcomings where improvements are required."
"Azure OpenAI should use more specific sources like academic articles because sometimes the source can't be found."
"The product must improve its dashboards."
"Latency performance is a major part. And I'm seeking support for multiple models that handle text, images, videos, and voice. I'm from India, and I'm looking for more support in Indian languages. There are 18 official languages and many more unofficial. We need support for these languages, especially in voice moderation, which is not yet available."
"There are certain shortcomings with the product's scalability and support team where improvements are required."
"Since we don't train the model on our data, it's a struggle to ensure OpenAI answers questions exclusively from our data. During user testing, we found ways to make the system provide answers from outside sources."
"The solution's response is a bit slow sometimes."
"If we could include our existing Python or R code in DataRobot, we could make it even better. The DataRobot that we have is specific to an industry, but most of the time we would have our own algorithms, which are specific to our own use case. If we had a way by which we could integrate our proprietary things into DataRobot with a simple integration, it would help us a lot."
"The business departments will love to work with DataRobot because they use the tool to investigate their data, such as targeting what they want to investigate. They don't need any data scientists near them. They can investigate at eye level and bring into the BI tool, or can bring it to the data scientist. Data scientists can use this tool to bring increase the solution to the maximum. All the others can use it, but not to the maximum."
"Generative AI has taken pace, and I would like to see how DataRobot assists in doing generative AI and large language models."
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Azure OpenAI is ranked 2nd in AI Development Platforms with 24 reviews while DataRobot is ranked 13th in AI Development Platforms with 3 reviews. Azure OpenAI is rated 8.0, while DataRobot is rated 8.6. 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 DataRobot writes "Easy to manage jobs and see the logs if there's any drift in a model, user-friendly, and the data munching is fast". Azure OpenAI is most compared with Google Vertex AI, Amazon SageMaker, Microsoft Azure Machine Learning Studio, Hugging Face and Replicate, whereas DataRobot is most compared with Amazon SageMaker, RapidMiner, Microsoft Azure Machine Learning Studio, Datadog and Hugging Face. See our Azure OpenAI vs. DataRobot report.
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