We performed a comparison between Azure OpenAI and OpenVINO 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."Generative AI or GenAI seems to be the best part of the solution."
"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 easy to use because the endpoints are created, and we just need to pass our parameters and info."
"Azure OpenAI is very easy to use instead of AWS services."
"The high precision of information extraction is the most valuable feature."
"We can use the solution to implement our tasks and models quickly."
"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 solution has a very drag-and-drop environment. Instead of coding something from scratch or understanding any concept in extensive depth before deployment, this is good. Plus, they have an auto dataset, which means you can choose any dataset they have instead of providing your own. So that's also pretty nice."
"The initial setup is quite simple."
"The features for model comparison, the feature for model testing, evaluation, and deployment are very nice. It can work almost with all the models."
"The inferencing and processing capabilities are quite beneficial for our requirements."
"There are certain shortcomings with the product's scalability and support team where improvements are required."
"I faced one issue with Azure OpenAI: My customer wanted more clarity on the pricing. They were not able to get proper answers from the documentation or the pricing calculator. I suggest that Microsoft maintain standardization in the pricing details published in the documentation and the pricing calculator."
"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 is room for improvement in their support services."
"We encountered challenges related to question understanding."
"The solution's response is a bit slow sometimes."
"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."
"Deployment was slightly complex for me to understand."
"It has some disadvantages because when you're working with very complex models, neural networks if OpenVINO cannot convert them automatically and you have to do a custom layer and later add it to the model. It is difficult."
"The model optimization is a little bit slow — it could be improved."
"At this point, the product could probably just use a greater integration with more machine learning model tools."
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Azure OpenAI is ranked 2nd in AI Development Platforms with 25 reviews while OpenVINO is ranked 11th in AI Development Platforms. Azure OpenAI is rated 8.0, while OpenVINO 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 OpenVINO writes "A free toolkit providing improved neural network performance". Azure OpenAI is most compared with Google Vertex AI, Amazon SageMaker, Microsoft Azure Machine Learning Studio, Hugging Face and Wit.ai, whereas OpenVINO is most compared with TensorFlow, PyTorch, Google Cloud AI Platform, Google Vertex AI and Microsoft Azure Machine Learning Studio. See our Azure OpenAI vs. OpenVINO 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.