We performed a comparison between Azure OpenAI and IBM Watson Machine Learning 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."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."
"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."
"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."
"Azure OpenAI is useful for benchmarking products."
"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."
"It is easy to integrate and develop a solution. Most customers are concerned about the security of their data and how cost-effective it is. We have developed some methodologies so that our customers will not be charged too much for these OpenAI services but will still get the same kind of performance and results. It's all developed on Azure, so customers also see its benefit."
"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."
"Azure OpenAI is very easy to use instead of AWS services."
"The solution is very valuable to our organization due to the fact that we can work on it as a workflow."
"I was particularly interested in trying the AutoML feature to see how it handles data and proposes new models. The variety of models it provides is impressive."
"It has improved self-service and customer satisfaction."
"The most valuable aspect of the solution's the cost and human labor savings."
"Scalability-wise, I rate the solution ten out of ten."
"It is has a lot of good features and we find the image classification very useful."
"There are certain shortcomings with the product's scalability and support team where improvements are required."
"There is room for improvement in their support services."
"Azure OpenAI will be expensive if you want to implement it as a permanent solution for a customer."
"Deployment was slightly complex for me to understand."
"Our customers are worried about data management, ethical, and security issues."
"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 needs to accommodate smaller companies."
"We encountered challenges related to question understanding."
"Honestly, I haven't seen any comparative report that has run the same data through two different artificial intelligence or machine learning capabilities to get something out of it. I would love to see that."
"They should add more GPU processing power to improve performance, especially when dealing with large amounts of data."
"The supporting language is limited."
"In future releases, I would like to see a more flexible environment."
"Scaling is limited in some use cases. They need to make it easier to expand in all aspects."
"If I consider how we want to use it in our organization, certain areas of improvement can be addressed. For instance, we want to use it with Generative AI, not like ChatGPT, but in a way intended for industrial use."
Azure OpenAI is ranked 2nd in AI Development Platforms with 24 reviews while IBM Watson Machine Learning is ranked 9th in AI Development Platforms with 6 reviews. Azure OpenAI is rated 8.0, while IBM Watson Machine Learning is rated 8.0. 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 IBM Watson Machine Learning writes "A highly efficient solution that delivers the desired results to its users". Azure OpenAI is most compared with Google Vertex AI, Amazon SageMaker, Microsoft Azure Machine Learning Studio, Hugging Face and TensorFlow, whereas IBM Watson Machine Learning is most compared with Google Cloud AI Platform and TensorFlow. See our Azure OpenAI vs. IBM Watson Machine Learning 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.
