Azure OpenAI Reviews

I was freelancing for a company that wanted me to make tutorials on how the platform can be used. So, here are just a few model-building video tutorials I made from the platform. That's pretty much it.

It's very easy and convenient to use compared to others. It has good documentation, and it's very easy to follow. So somebody using it for the first time finds it very convenient.

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.

Maybe Azure OpenAI could provide a few video tutorials, in addition to the documentation. If they want to make it easier for somebody to do it for the very first time, providing video tutorials might be a good idea.

So, I would like to have a tutorial added for new users. 

I have only worked for around a month or so.

I would rate the stability a nine out of ten. It is very stable. 

I would rate the scalability a seven out of ten. 

I took up a course that gave me access to Amazon. But when I compare OpenAI with Google and Amazon because I work with both Google and Amazon, I would put OpenAI, then Google, then Amazon.

So, Azure OpenAI is on top of my list. They've got a very user-friendly platform, so that works best. Amazon is slightly complex. Google provides video tutorials, but somehow Azure has a better UI.

I would rate my experience with the initial setup a seven out of ten, where one is difficult, and ten is easy. 

Deployment was slightly complex for me to understand. So, my senior was working on it, but I did not directly deploy it. The instructions are very clear on how to deploy it, so it is fine, and it doesn't take a lot of time. It hardly takes a few minutes, I think, d depending on the data. If the dataset is very big and if the model is complex, then maybe deployment will take more time. But if it's something very simple and basic, deployment was fine.

I would suggest you should give it a try. Overall, I would rate the solution an eight out of ten. 

The main use case for Azure OpenAI is invoice processing. The first step is to recognize the text from images through Azure Cognitive Services, and then utilize Azure OpenAI to extract relevant information from the text. It provides more accurate information extraction compared to Azure Recognizer. This automation helps streamline the accounting process.

The high precision of information extraction is the most valuable feature. It enables the accurate extraction of information from various types of documents, including contracts, invoices, CDs, and fiscal documents.

Azure OpenAI needs to be updated quickly to keep up with rapidly changing technologies. There are no available updates of information that are currently provided. It is important to integrate newer technologies and ensure accurate information is available for seamless operation.

It is a recently launched platform, so I have used it for a couple of months now.

I didn't face any issues regarding the stability. I would rate it nine out of ten.

I would rate the scalability ten out of ten.

Microsoft offers very good support services. If there is any issue, regarding the operation or during deployment, you can reach out to their global IT department for assistance. I would rate it nine out of ten.

Positive

The initial setup was easy. I would rate it eight out of ten. It is simple to use. There are certain security concerns that may arise with multinational companies, that require approval from IT department to use it. Overall, it is not a difficult process.

We received notification that our team works on the deployment of the solution on the preferred cloud.

The cost structure depends on the volume of data processed and the computational resources required. There might be additional costs for private cloud usage and security considerations.

It is a useful solution that offers a variety of purposes. Developers can benefit from improvements in the system that would align with current technologies. Different departments, such as marketing, accounting, and finance can already use Azure OpenAI as a helpful assistant. I would rate it nine out of ten.

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.

The solution allows you to work through the extraction and summarization of unstructured documents.

The solution needs to accommodate smaller companies. 

I have been using the product for four months. 

I rate Azure OpenAI a nine out of ten. 

I rate the product's scalability a three out of ten. 

Azure OpenAI's deployment is straightforward. It is quick to deploy and can be completed in weeks. We had three resources deploying it. 

The tool costs around 20 dollars a month. 

I rate Azure OpenAI a nine out of ten. 

We are assisting our customers in deploying a commercial universal AI solution aimed at aiding them in researching and managing their internal company policies and regulations. To do this, I've extracted all the relevant documents from the HR department and created conversational interfaces for our clients. These interfaces are integrated into various platforms like Microsoft Teams, allowing everyone within the company to interact with the AI.

Its main use for indexing documents and assembling information is highly effective. Previously, we had to meticulously map out each process and step, essentially creating a chatbot for the task.

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.

We encountered challenges related to question understanding. These instances occur when questions are not phrased precisely, resulting in problematic answers. Microsoft is actively addressing this issue and working diligently on improving it.

I have been working with it for six months now.

We have nearly thirty customers using our system, and I can't recall any instances where they've encountered stability issues.

I would rate its scalability capabilities seven out of ten.

We have a direct connection with all the technical support staff in the support area. I would rate it nine out of ten.

Positive

We tried integrating Google in the past, but it didn't proceed as planned so we just stopped it.

The initial setup was straightforward.

The pricing is acceptable, and it's delivering good value for the results and outcomes we need.

My advice is to pay close attention to the content's quality before indexing it within OpenAI. If the documents provided lack good quality, they'll end up with incorrect answers. This is particularly important because the initial setup is not inexpensive and it involves significant investments. Overall, I would rate it nine out of ten.

We use the solution for training. We did a POC. We use it for some hackathon projects we have been working on.

The solution has improved our development process. When we integrate with OpenAI, we get immediate responses for what kind of code or logic we must use.

GPT was useful for our projects.

The UI could be a little easier. The prompts must be updated.

The product is not stable. We get different results for the same prompts. The stability must be improved. However, it is common across any AI tool we use.

The product is pretty much scalable. It helped us scale some of our projects. The internal teams use the tool for projects.

The setup is easier compared to AWS. The tool can be deployed on the cloud.

We use the API calls to integrate OpenAI into our existing workflows. I use API calls. We used the tool for testing purposes for a small project. It was not given to the end users. People who want to use the solution must go through its capabilities. Though AI is available in the market, not everyone is exploring it. The tool is an advanced alternative to Google Search. It helps with development and coding by providing prompt responses. Overall, I rate the product a nine out of ten.

We are currently exploring the solution's LLM chat and question-and-answer-based endpoints.

The most valuable feature of the solution is the accuracy of ChatGPT. It is something we cannot reproduce with any open-source LLM. Azure OpenAI is easy to use because the endpoints are created, and we just need to pass our parameters and info.

Azure OpenAI will be expensive if you want to implement it as a permanent solution for a customer. I have explored Azure OpenAI from a purely LLM perspective. Its endpoints are currently enough for us to communicate with their ChatGPT instance and get results. I don't know if Azure has anything implemented for images, videos, and other endpoints.

We have been exploring ChatGPT 3.5 and 4 versions for one and a half years.

Around 20 to 50 users were using Azure OpenAI for one of our projects.

Whenever we encounter issues, we try to raise them on the portal, and we get a resolution from there.

Microsoft takes care of the deployment. We just get our instance, and we have to communicate with it.

If you consider the long-term aspect of any project, Azure OpenAI is a costly solution. However, the solution is cheap if you just want to see results or try some POC in the initial stages. This is because you don't need to spin up your instance; you can just consume things and see the results.

Azure OpenAI is a straightforward solution. After configuring it, you will get your endpoints. You then need to call the endpoints and pass the details. Azure OpenAI is a straightforward tool that is implemented in such a way that even a fresher or junior developer can learn to use it easily.

Overall, I rate the solution an eight out of ten.

I use Azure OpenAI to create message dashboards for my company.

The most valuable feature of Azure OpenAI stems from the GPT-3.5 models it provides to its users. The information that I provide is based on the information I found through research. I have not started to use the solution for the development part.

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. It would be great if Azure OpenAI could increase the limit of the knowledge of its chatbot. If I have datasets for fine-tuning, the chatbot can only answer the user's queries related to training data, meaning the chatbot would not provide any knowledge to its users from the outside world.

I have been using Azure OpenAI for maybe a month.

I work in a company involved in some business related to messaging, where I did not have a reason to think about scalability options provided by the solution.

I have not contacted the solution's technical support yet since I am still involved in some research related to the product.

I have experience with LangChain. LangChain uses OpenAI.

The documentation provided by Azure OpenAI is clear enough. Based on my research, I think the product's initial setup phase would be easy.

The solution is deployed on the cloud services from Azure.

Though in my company, we are in the process related to the deployment of Azure OpenAI, it has not been deployed yet.

I want Azure OpenAI since it is the best solution related to language processing.

The only suggestion I can provide to those who plan to use Azure OpenAI is to consider providing the tool with clear prompts. Azure OpenAI is one of the best tools and easy to use.

Sometimes, when I try some prompts, Azure OpenAI fails to understand them. Overall, Azure OpenAI is a really helpful tool.

I rate the overall solution a nine out of ten.

When I write documentation, I use the solution for translating anything and researching.

Azure OpenAI is useful for benchmarking products. We can search for all metrics with AI tools and compare our products with other products.

The solution’s stability could be improved. Azure OpenAI should use more specific sources like academic articles because I can't find the source.

I have been using Azure OpenAI for more than a year.

I rate the solution a nine out of ten for stability.

I rate the solution’s scalability a seven out of ten.

The solution’s initial setup is very easy.

I can deploy the solution by myself in a few seconds.

We pay a licensing fee for Azure OpenAI. The solution's pricing is normal worldwide but expensive in Turkey because Turkey's currency is different.

Azure OpenAI provides me with a lot of benefits. It's quick and saves me time.

Overall, I rate the solution an eight out of ten.