Azure OpenAI Reviews

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.

We use the solution for Document Intelligence, ChatGPT, and NLP.

Azure OpenAI is very easy to use instead of AWS services. And people are more aware of Azure OpenAI. ChatGPT was acquired by Microsoft, and people want to use the ChatGPT model with Azure OpenAI.

Azure OpenAI is not available in all regions, and its technical support should be improved.

I have been using Azure OpenAI for one year.

Azure OpenAI is a stable solution.

I don't like Microsoft's technical support. Microsoft's support puts our Severity A ticket in the queue, and we have to wait eight hours for its resolution, which is quite annoying.

Negative

You need to send a request to Microsoft. Not all companies have a Microsoft enterprise subscription. You need to enable the Azure OpenAI services specifically for your subscription. You can deploy Azure OpenAI services only after it is approved. Azure OpenAI has limitations as it is not available in all regions. There are specific regions where you can deploy Azure OpenAI, which is a big limitation. It's difficult for us to deploy Azure OpenAI in regions without firewalls.

The solution's pricing depends on the services you will deploy. The solution's ChatGPT service would have a different price depending on the number of tokens or requests. If you go for machine learning, it comes at a different price. Azure OpenAI doesn't have a fixed price.

The pricing depends on the services you deploy, the amount of data you push, and the endpoint output. For example, if you increase the memory of a virtual machine, its cost will increase. Azure OpenAI will show you the cost based on the services you use.

You can definitely use Azure OpenAI, but you need to study the solution and the use cases you need the solution to meet. In Azure OpenAI, you have many services like ChatGPT and Document Intelligence. If you know what kind of services you need from Azure OpenAI, things will be easier. Otherwise, you need to study a little bit.

The solution's language model customization improved the applications of the end users. Azure OpenAI integrated with our existing cloud infrastructure.

Overall, I rate the solution a nine out of ten.

We are using Azure OpenAI in programming, particularly for generating text and image content. For coding purposes, we use Copilot for writing code in Python. The use depends on client requirements, especially when working with text or image processing.

Some valuable features we utilize include the search functionality and Copilot for coding. The AI search functionality is particularly effective, as it creates summaries from data. Azure's integration with OpenAI's GPT is beneficial as well, especially for text generation tasks.

Azure needs to work on its own model development and improve the integration of voice-to-text services, particularly for right-to-left languages such as Arabic and Urdu. The accuracy in these languages requires improvement.

I have been working with Azure OpenAI for about one and a half to two years.

The solution works fine, particularly for enterprises or even some small enterprises. However, Microsoft needs to implement its solutions more in its own products to demonstrate their effectiveness.

For scalability, I would rate Azure OpenAI around six or seven on a scale of one to ten. The scalability depends on whether the application is multimodal or uses a single model.

Microsoft offers phone or chat support, however, they need to implement AI chatbots for technical support. It is important for organizations like Microsoft to apply OpenAI solutions within their own structures.

Neutral

I moved to another vendor for firewall solutions, specifically mentioning ZenoWatt initially, yet clarified that I am currently working more with cloud solutions.

The setup can be straightforward if you are familiar with Azure. However, Microsoft sometimes complicates the process with unnecessary configurations which can lead to errors. Their security implementations make the process a bit complex.

The pricing is standard and similar to other cloud-based systems. There might be minor differences. Generally, the costs are comparable across platforms.

We consider solutions from Meta and the upcoming technologies from Elon Musk's GROK, along with some Chinese companies that are emerging prominently.

I would rate the overall solution five to six out of ten, depending on whether it's being used for a single or multimodal application. Azure can be a suitable choice for clients with small-scale data requirements.

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.

I use the platform for troubleshooting issues. When I encounter a problem, I turn to OpenAI to understand the reasons behind the issue and how to resolve it.

I find the platform's accessibility across all devices to be highly valuable. Additionally, the paid version offers a wide range of GPTs for various tasks, including technical problem-solving, scientific research, communication improvement, writing, art, and design. These GPTs use ChatGPT to build specific tools that leverage AI to expedite work processes. 

The product could be more user-friendly in terms of features. There could be an ability to generate visual data, such as architecture diagrams. This could enhance its utility for various use cases.

I have been working with OpenAI for for approximately two to six months.

The product has been highly stable. I have not encountered any outages so far.

Since OpenAI is cloud-based, it can scale to accommodate any number of users. Each user needs a unique email ID, but otherwise, it is quite flexible in terms of scalability. Approximately 200 or more users in our organization are utilizing it regularly. 

The free version does not offer support. To receive support, one typically needs to purchase a monthly subscription, which costs $19.

OpenAI is a cloud-based solution, so there is no need for local setup. It operates on the cloud and is accessible via cloud-based services.

The platform generates a return on investment in terms of efficiency in problem-solving and task automation has contributed to productivity gains.

While the product meets our business requirements well, I consider it relatively expensive, especially for individual users like myself. However, as I become more accustomed to its benefits, it may become more affordable over time.

I would recommend OpenAI to anyone who can afford it. Its versatility makes it incredibly useful for technical problem-solving, content creation, data analytics, and more. It is a powerful tool for enhancing productivity across various domains.

It is at the forefront of the AI trend, providing powerful tools that leverage AI to streamline workflows and improve efficiency.

I rate it a seven out of ten. 

I'll provide feedback on additional features after the project is completed. I think it would be better to comment on that after the implementation is finished.

I have been testing this solution for the past month. 

The deployment is not finished yet. To assess performance and stability, the project needs completion. Currently, our professional service is actively involved, managing tasks related to services and users in the ongoing termination process.

Currently, I'm in constant communication with them. They are professional, helpful, and highly experienced.

Positive

They need to simplify the implementation process. I've observed that sometimes the professional service is focused on the database, especially around log shipping, and it can be challenging. I'm actively involved in the deployment process, but it's carried out by our professional service. Our plans are implemented through this service, acting as intermediaries between our clients and the professionals. The implementation typically takes around a month, but various issues, such as management, resource, and other challenges, may arise during the deployment.

One notable difficulty we face is the lack of exceptional resources for deploying the solution in our plans. Despite encountering challenges, our satisfaction with the professional service remains high. They are dedicated to implementing the solution effectively.

I would also rate it a ten overall. It's scalable and easy to deploy. However, I have some concerns. I noticed there are no instructional videos or guides on the network portal for initial configurations. There is limited information available, and this is a concern for me. I would like to see more resources and guides to address these issues.

Regrettably, this product remains incomplete, and the interim phase is still pending. It is challenging to determine its effectiveness due to some significant license initial issues.

We can use the solution to implement our tasks and models quickly.

The product must improve its dashboards. I would like to know how many tokens my requests use and how accurate the search is. We are using Python language to find out about it.

I have been using the solution for six months. I am using the latest version of the solution.

I rate the tool’s stability a ten out of ten. I do not have any problems with it.

About 5000 people use the tool in our organization. I rate the tool’s scalability a six out of ten because it doesn’t have automatic installation options.

We have done some POCs with AWS Bedrock and some AI products from Google. We chose Azure OpenAI because we have a preference for the vendor. All our infrastructure is deployed on Azure.

We are maintaining the solution, but the maintenance is not on OpenAI services. We maintain the Python code that we embedded. Our technical team has five people, including two engineers and two data scientists.

The response time of our call centers has improved. The team is using the language models to ask simple questions.

I would recommend the tool to others. Overall, I rate the solution an eight out of ten.

We used the model to produce the dashboards. They created them, but we weren't satisfied because they weren't interactive for decision-making and governance. We integrated Azure with SharePoint and AI to create an interactive model. That's what we did with Azure for our specific project.

We use Azure, but what we put in place is not just Azure. We created interactive dashboards. These allow people to instantly understand the situation when they see a red code, for instance. This enables governance to make a strong diagnosis of the situation and resolve it. 

It also helps integrate all the digital elements that affect decision-making in project resolution. This allows for evaluation and restructuring of project scope with an agile approach, and to put in place solutions to integrate stabilizing elements. 

The project I completed for this specific issue last year was a big success and is now being used by the entire department.

I'm an IT integrator. When I use Azure, if the model meets the need, I use what the system offers.

Our approach is stronger due to the algorithm we use. The system manages the equilibrium between different project environments. Many projects are executed in a stable environment, but when you create reorganizations, you destabilize the environment. Agile methodologies are necessary in such cases, but managing projects with MS Project in the field involves a stable environment. 

When these two environments interact, it creates resistance and digitalizing elements that hinder project realization. My mandate was to eliminate these obstacles and integrate the stabilizing and unstable environments. This ensures the establishment of a stable environment for the projects being realized. We created a significant part of the project to achieve this and replanned to ensure we could restabilize the project environment. We developed new management techniques and integrated them with various AI models.

For my needs, when working with interactive dashboards, it's expensive. I would prefer a system that provides alternative dashboard options or allows me to go directly into the program and pinpoint problems for decision-makers.

I'm an IT employee implementing solutions for clients who have specific requirements. As a Guidewire PolicyCenter status at Guidewire, I can manage teams with up to 200 professionals. 

This allows me to integrate many specialists and multi-disciplinary specialists into my teams and create strong solutions for clients.

It's good for a regular user, but for someone like me who creates and implements solutions, it is okay. 

The technical team is very helpful and easy to work with.

Positive

Throughout my career, I've been an expert in IT integration with a Guidewire approach. I work with strategies and implement them using Guidewire techniques and IT solutions. I've integrated solutions both vertically and horizontally in projects for clients. I've also created interactive dashboards with AI, using it as an expert system. This allows for a fully integrated solution within multi-project environments with complex issues. I began this in 1988.

The first project I worked on after my master's was presented by the federal government, Environment Canada, for the St. Lawrence River and the Great Lakes. They had a big budget and asked me to conceptualize all the programs that integrated many departments.

They asked me to reorganize and restructure the project to manage quality and ensure continuity after projects were completed. They wanted to ensure technology and budget were used effectively.

We have recently put in place SharePoint. We restructured the system with Microsoft 365 and integrated it with budget and document management. We organized all the applications. 

Before I arrived, many directors had uncontrolled access to the budget. We implemented a governance system similar to the Business Development Bank to ensure budget control. We integrated everything into Microsoft 365, including MS Project and SharePoint. We used insights to facilitate Kubernetes assessment and the assessment of projects in the field.

If I compare it with other IT I've worked with, I like to work with Appian. I think it's very strong, and for me, it's a benchmark to compare others. I also like to work with MuleSoft. It's another approach, but very interesting for me. When I compare with Microsoft 365, it's good but doesn't necessarily allow me to resolve all the issues I have. With Appian, we can find the solution we need; any kind of requirement we have, we're able to find an approach or solution within the system.

I have used Azure. I have forty years of experience in reorganization and business transformation. When IT can't directly meet my needs, I ask my technicians and analysts to examine the specific case for the project. In this instance, we used Azure to create interactive dashboards. They reprogrammed and worked with SharePoint to integrate Azure into the AI, the internal artificial intelligence.

The integration and the solution modeling can be complex. 

The pricing really depends on the specific requirements and underlying needs. For example, if the goal is to implement innovative solutions for the future or to improve productivity in decision-making and governance, then the cost might be justified. 

In a recent project, I achieved strong results using only 60% of the allocated budget. The client was impressed. They were curious about my approach, but I assured them it was simply my way of working.

I'm an IT integrator. When I use Azure, if the model meets the need, I use what the system offers. I use any kind of IT that I can, depending on the needs and the strategy we want to implement. IT can offer some services, but they have a suite of services that they don't offer, and we have to create and integrate with the IT. 

I work with my team to upgrade the IT we use. We integrate it with, for example, artificial intelligence like OpenAI to resolve or address the specific issue I want to solve. That's my way of working. IT can't stop me from putting a solution in place. I prefer to add to it or create a completely operational solution that can satisfy the client's exact needs.

For example, the problems in a specific project were major. When I finished, I had implemented a solution that answered the project's/client's exact needs. We reorganized the entire project structure, which allowed the company to use the IT we adapted. We put in place specific applications for governance and project management in the field. 

As a program manager, I communicate the needs and the desired results and evaluate what technology can offer based on the requirements. People offer me solutions. If it's on Azure, that's okay. If it's on Microsoft 365, that's fine too. 

I have techs who work for me and present solutions that I assess with them, considering the complexity of integrating all the necessary applications. If the solution satisfies my requirements, I authorize it, and we structure the project. We integrate all the issues and stabilizing elements into the project scope and manage it like any other project.

Azure OpenAI, for me, it's a component I use in my solution to ensure the application I want is realized. That's my approach. I'm a program manager, a person who manages IT architecture, project management, and change management. The requirements of the clients are my guide. Based on that, I will organize the solution.

I've always modified Azure to create interactive solutions. But it depends on the kind of application you want. I can recommend it for standard documentation, but not for developing innovative solutions. My requirements are more advanced.

Overall, I would rate it a seven out of ten.