Azure OpenAI Service

Score8.5 out of 10

8 Reviews and Ratings

What is Azure OpenAI Service?

Azure OpenAI Service, a service from Microsoft's Azure suite available in preview, includes pre-generated AI models that enable users to apply advanced coding and language models to a variety of use cases, enabling new reasoning and comprehension capabilities for building applications. Users can apply these coding and language models to a variety of use cases, such as writing assistance, code generation, and reasoning over data.

1,478 installations of 5,175

#2 most frequent

Information

14.8%

765 installations of 5,175

#3 most frequent

Finance and Insurance

13.7%

708 installations of 5,175

Dipak Kawale View profile

ML Engineer in Engineering at Sankey Solutions (51-200 employees employees)

Use Cases and Deployment Scope

We use GPT 4-o deployment of Azure OpenAI for Generative AI application where we have utilized this to generate recommendation for products, chatbot for financial insights and many more. this helps in reducing manual effort and adds more engagement with a RAG approach which gives response based on knowledge base.

Pros

Generating SQL
Generating Images
Sensible Response

Cons

Generating correct Mathematical Calculation
Generating Optimize code for CYPHER Query Language
Text in a generated Image should be correct

Return on Investment

PE Firms Got Benefited by Gen AI application Helped them to reduced
of 80% time in research
OpenAI helps retail industry to get the recommendation on products
It helps us too, to solve chunks of problems easily. Increases our efficiency by 10x

Usability

Alternatives Considered

Meta Llama 2, Anthropic Claude and Vertex AI

Other Software Used

AWS Glue, Docker, Google Cloud Dataproc

Verified User

Team Lead in Engineering (501-1000 employees employees)

Use Cases and Deployment Scope

We realized that our employees are using ChatGPT to accelerate their daily work. That's a good thing as it shows they're embracing new technologies to improve productivity. However, ChatGPT being 3rd party, that usage carries the risk of leaking customer sensitive data.

That's why we decided to setup & operate an internal ChatGPT portal so our people can leverage AI power while keeping our data private.

Pros

Well documented API
Multiple models to choose from
Advanced networking options

Cons

More examples would be helpful, especially when it come to token counting & summarizing
Pricing is not really straightforward to estimate as it's based on token count
Complete privacy requires special agreement with Microsoft

Return on Investment

Our test group of 100 people created more than 200 conversations within the first day
People were excited & asked to be included to the test group once words spread that we have an internal ChatGPT portal
People started to create & share their own assistants (prompt engineering) for various purposes like code review, marketing, email, etc.

Usability

Other Software Used

AWS Secrets Manager, Amazon Elastic Container Service (Amazon ECS), MongoDB Atlas

Verified User

Manager in Information Technology (5001-10,000 employees employees)

Use Cases and Deployment Scope

Azure OpenAI is sued for O365 including sharePoint, teams, exchange & OneDrive. We also use it for voice recordings, VDI & AI.

Pros

Provides additional guard rails by leveraging MS Azure
Ability to spin up different models quickly and efficiently

Cons

Specific models' capacity limited have to span multiple regions for capacity.
Better support for Open AI, knowledge limited within support.

Return on Investment

We are currently leveraging with AI in in AWS for a total solution.
Studio has worked well allowing users to interact without having to code and interact via an API.

Usability

Other Software Used

Azure Virtual Desktop, Verba Recording System

Verified User

C-Level Executive in Corporate (1-10 employees employees)

Use Cases and Deployment Scope

I am a part of Microsoft for Startups Founders Hub, so I have access to latest models on Azure OpenAI Service. I use them to accomplish my research related tasks like disease findings in crops, taking summary of them with possible treatments as well. I also use it to generate texts for articles and business conversations.

Pros

It's generative AI like ChatGPT but you get advanced models, so it's more powerful.
You can use API to automate the process of Generative AI tasks.
It also provides a sample script code on how we can use the API.

Cons

The user interface is similar to the Azure, so it's bit laggy, they should improve it.
The chat models sometimes return nothing, I guess they are still testing them.
The models we use have quota limitation on tokens and number of requests.

Return on Investment

Honestly, I just started using it a few months ago, and I haven't seen any major benefits.
It has almost similar capabilities as free version of ChatGPT, so it's worth paying for chat models unless we need to use API.
ROI has not been impacted at all, as I mostly use free version over this to avoid higher charges.

Alternatives Considered

ChatGPT, VEED.IO and Meta Llama 2

Other Software Used

ChatGPT, Meta Llama 2, VEED.IO

Azure OpenAI Service

What is Azure OpenAI Service?

Categories & Use Cases

Product Demos

Most Frequent Users

Professional, Scientific, and Technical Services

Information

Finance and Insurance