We performed a comparison between Azure OpenAI and Google Cloud AI Platform 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 product saves a lot of time."
"The product's initial setup phase was pretty easy."
"Azure OpenAI is easy to use because the endpoints are created, and we just need to pass our parameters and info."
"The high precision of information extraction is the most valuable feature."
"Azure OpenAI is useful for benchmarking products."
"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 product is easy to integrate with our IT workflow."
"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."
"Some of the valuable features are the vast amount of services that are available, such as load balancer, and the AI architecture."
"The initial setup is very straightforward."
"Since the model could be trained in just a couple of hours and deploying it took only a few minutes, the entire process took less than an hour."
"A range of a a wide range of algorithms, EIM voice mails, which can be plugged in right away into your solution into into into our solution, and then have platform that provides know, to to come up with an operational solution really quick."
"The solution is able to read 90% of the documents correctly with a 10% error rate."
"On GCP, we are exposing our API services to our clients so that they send us their information. It can be single individual records or it can be a batch of their clients."
"I think the user interface is quite handy, and it is easy to use as compared to the other cloud platforms."
"Azure OpenAI is not an optimized tool yet, making it one of its shortcomings where improvements are required."
"We encountered challenges related to question understanding."
"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."
"Azure OpenAI should use more specific sources like academic articles because sometimes the source can't be found."
"There are certain shortcomings with the product's scalability and support team where improvements are required."
"I have found the tool unreliable in certain use cases. I aim to enhance the system's latency, particularly in responding to calls. Occasionally, calls don't respond, so I want to improve reliability."
"Azure OpenAI is not available in all regions, and its technical support should be improved."
"We are awaiting the new updates like multi-model capabilities."
"The solution can be improved by simplifying the process to make your own models."
"The initial setup was straightforward for me but could be difficult for others."
"At first, there were only the user-managed rules to identify the best attributes of the individual. Then, we came up with a truth set and developed different machine learning models with the help of that truth set, so now it's completely machine learning."
"I think it's the it it also has has evolved quite a bit over the last few years, and Google Cloud folks have been getting, more and more services. But I think from a improvement standpoint, so maybe they can look at adding more algorithms, so adding more AI algorithms to their suite."
"One thing that I found is that Azure ML does not directly provide you with features on Google Cloud AI Platform, whereas Vertex provides some features of the platform."
"It could be more clear, and sometimes there are errors that I don't quite understand."
"Customizations are very difficult, and they take time."
Azure OpenAI is ranked 2nd in AI Development Platforms with 22 reviews while Google Cloud AI Platform is ranked 6th in AI Development Platforms with 7 reviews. Azure OpenAI is rated 8.0, while Google Cloud AI Platform is rated 7.8. 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 Google Cloud AI Platform writes "An AI platform AI Platform to train your machine learning models at scale, to host your trained model in the cloud, and to use your model to make predictions about new data". Azure OpenAI is most compared with Google Vertex AI, Amazon SageMaker, Microsoft Azure Machine Learning Studio, Hugging Face and IBM Watson Studio, whereas Google Cloud AI Platform is most compared with Microsoft Azure Machine Learning Studio, IBM Watson Machine Learning, Google Vertex AI, Hugging Face and Amazon SageMaker. See our Azure OpenAI vs. Google Cloud AI Platform 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.
