Azure OpenAI Reviews

Name: Azure OpenAI
Brand: Microsoft
Rating: 4.0 (32 reviews)

Vendor: Microsoft

4.0 out of 5

32 reviews
93% willing to recommend

145 followers

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What is Azure OpenAI?

Azure OpenAI integrates advanced language models with robust security for precise information extraction and task automation. Its seamless Azure integration and drag-and-drop interface simplify implementation and enhance accessibility.

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Azure OpenAI is the #1 ranked solution in top AI Development Platforms. PeerSpot users give Azure OpenAI an average rating of 8.0 out of 10. Azure OpenAI is most commonly compared to Microsoft Azure Machine Learning Studio: Azure OpenAI vs Microsoft Azure Machine Learning Studio. Azure OpenAI is popular among the large enterprise segment, accounting for 65% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a financial services firm, accounting for 15% of all views.

Helped 842,296 peers since 2012

Featured Azure OpenAI reviews

Viswanath Barenkala

Associate Vice President at State Street

Instead of a feature, the GPT-4 model has been most beneficial for automating tasks. We transitioned from GPT-3.5 to GPT-4 and actively use it. However, we face limitations due to geographic availability, subscription constraints, and rate limiting, which we are currently negotiating and working towards optimizing. While we haven't formally benchmarked Azure OpenAI's language understanding against industry standards, we find it performs well about 70-80% of the time. Occasionally, we need to refine our queries and adapt our systems accordingly to improve accuracy and effectiveness.

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Sohaib Gill

Sr. Machine Learning Engineer at Hyly.AI

We are using both servers. I use Azure OpenAI on our on-premises server. Since OpenAI is a cloud service, we cannot download the Azure OpenAI models on our server. So, we have to use their cloud through the API. Currently, there is a lot of competition in the LLM area. The person who tries to start with LLMs must try different services, including Azure OpenAI. They should start with the cheapest model, which is GPT-3. They should stick to that model if it works for them and responds well to their requirements. They can also try other cheap API services that respond more accurately to their requirements. I would suggest trying different models or API services to start with. When you start with the application, it is initially very easy to learn. You just have to write a prompt in simple English language to get the output from the solution. You can write anything; the prompt and your model will yield good results. You can start easily with the solution, but learning more advanced features of prompt engineering will take some time. Overall, I rate the solution an eight out of ten.

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Anup Karade

Associate Vice President at LTIMindtree

We have created our own platform called CanvasAI. It provides machine-learning plumbing and integration with your services. So, we've integrated Azure OpenAI through Canvas. We're also looking at some hard interface modeling from AWS as well. We access Azure OpenAI solutions for our business workflow via the platform, not directly from the service provider. There are security considerations we're working through with the security team, etc. Canvas provides the control plane, which handles RBAC for user registration and model management. For internal processes, we're using OpenAI to create partner call reports, like summarizing quarterly zip code data and other financial models. We also use it for legal and contract stuff, like comparing SOWs and contracts. For user experience, we've created a chatbot powered by OpenAI to answer HR, travel, and expense-related questions.

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Azure OpenAI mindshare

As of March 2025, the mindshare of Azure OpenAI in the AI Development Platforms category stands at 13.9%, down from 20.9% compared to the previous year, according to calculations based on PeerSpot user engagement data.

AI Development Platforms

PeerAnalyst reports based on Azure OpenAI reviews

Type	Title	Date
Category	AI Development Platforms	Mar 26, 2025	Download
Product	Reviews, tips, and advice from real users	Mar 26, 2025	Download
Comparison	Azure OpenAI vs Google Vertex AI	Mar 26, 2025	Download
Comparison	Azure OpenAI vs Microsoft Azure Machine Learning Studio	Mar 26, 2025	Download
Comparison	Azure OpenAI vs Amazon SageMaker	Mar 26, 2025	Download

Title	Rating	Mindshare	Recommending
Microsoft Azure Machine Learning Studio	3.8	7.6%	93%	60 interviews Add to research
Google Vertex AI	4.2	14.9%	100%	10 interviews Add to research

Valuable Features

Azure OpenAI's most valued features include high precision in information and data extraction, seamless integration with Microsoft tools, modular design for reduced computation time, and security. Users appreciate its ease of use, conversational capabilities, and language understanding. Its ChatGPT accuracy, drag-and-drop environment, scalability, information retrieval, and benchmark functionality are also highlighted. The platform supports efficient data processing, requires minimal training setup, and enhances productivity through AI-driven insights and analysis.

"I would rate it a nine out of ten."
"Azure's integration with OpenAI's GPT is beneficial as well, especially for text generation tasks."
"Its ability to understand and respond well to queries, including language translation for clients, is beneficial."

Room for Improvement

Azure OpenAI faces challenges in updates and integration with emerging technologies. Users cite data management and security concerns, repetitive responses, high latency, and issues with cost transparency. Improvements are desired in model fine-tuning, video tutorials, dashboard functionality, language support, and model availability. Users seek enhanced scalability, real-time support, and improved voice and text interactions. Clarity in pricing and documentation, along with greater reliability and reduced latency, are also requested.

"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."
"Maybe with the next release, the response will be more precise and more human-like."
"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."

ROI

Azure OpenAI improves productivity by 40-45% and reduces development time and costs through integration with GitHub Copilot and automation. Users experience a 30-40% cost reduction in various processes, including legal tasks. With faster implementation, projects complete in weeks instead of months. Cost savings arise from reduced need for expertise and utilization of efficient models pre-built by Microsoft. Call center responsiveness and digital metric insights enhance overall efficiency, contributing to favorable ROI and customer satisfaction.

Pricing

Azure OpenAI pricing is flexible and varies based on data volume, computational needs, and specific services deployed. The cost structure includes token-based payments for model use and may involve setup costs for private cloud and security. While some find the pricing high, especially in certain regions, others perceive it as competitive with similar cloud services. Enterprise agreements can offer preferred pricing, but financial controls are essential to manage potential cost escalations.

"We started with monthly payments, but we plan to switch to yearly billing once we've stabilized our solution."
"I rate the product pricing six out of ten."
"While the product meets our business requirements well, I consider it relatively expensive, especially for individual users like myself."

Popular Use Cases

Organizations primarily utilize Azure OpenAI for a range of tasks, including document analysis, chatbot development, enhancing internal communication, industry-specific automation, and customer service improvements. Key applications include invoice and document processing, generating text and code, predictive analytics, and creating interactive dashboards. Enterprise solutions address digital transformation across HR, legal, finance, and IT departments. Additional use cases involve streamlining healthcare documentation, insurance claim processing, and training through automation.

Service and Support

Many users find Azure OpenAI's support professional and responsive, though experiences vary. Some praise quick assistance and strong connections with technical staff. Others report slow responses and occasional unavailability of direct ticketing. Microsoft offers support through phone or chat, but delays occur, and AI chatbots are recommended. For substantive support, subscriptions are necessary. Rapid adoption outpaces available expertise, impacting accessibility. Technical support depends on individual needs, with cloud infrastructure receiving better attention than specific model-related issues.

Deployment

Azure OpenAI's initial setup is generally straightforward and easy for many companies, but some encounter complexities like security concerns, regional limitations, and access settings. Documentation is clear, yet deployment time varies. Some users face challenges with governance, compliance, and complex scenarios; however, cloud integration typically simplifies the process. Setup depends on expertise with Azure, with quick deployment possible for simpler applications while more intricate environments require additional time and resources.

Scalability

Azure OpenAI is generally considered scalable, with ratings varying from five to ten. Scalability is influenced by configuration, region, and user base size. While some report difficulties with high loads and capacity, others highlight its cloud-based advantages and improved token limits. Smaller organizations face cost issues, but larger deployments see positive ROI. Flexibility allows diverse applications, though regional limitations exist. Some users note seamless scaling, while others encounter challenges in practice.

Stability

Azure OpenAI receives mixed feedback on stability. Many users rate it highly, with scores mostly around nine out of ten, indicating satisfaction. However, some experience instability, rating it lower, often citing downtime and performance fluctuations. Occasional issues arise, such as inconsistent results and stability disruptions during peak times. Users acknowledge it's generally stable, but improvements are needed, particularly in consistency and reliability. Users report that it performs well across varying company sizes and usages.

These insights are based on the in-depth reviews provided by peers to help you make a better buying decision.

Download our Azure OpenAI Buyer's Guide for additional reliable information.

Review data by company size

By reviewers

By visitors reading reviews

Top industries

By visitors reading reviews

Financial Services Firm

15%

Computer Software Company

13%

Manufacturing Company

11%

Educational Organization

Government

University

Healthcare Company

Insurance Company

Comms Service Provider

Retailer

Energy/Utilities Company

Media Company

Real Estate/Law Firm

Construction Company

Non Profit

Hospitality Company

Wholesaler/Distributor

Legal Firm

Performing Arts

Consumer Goods Company

Outsourcing Company

Logistics Company

Pharma/Biotech Company

Recreational Facilities/Services Company

Transportation Company

Compare Azure OpenAI with alternative products

Learn more about Azure OpenAI

Azure OpenAI offers a comprehensive suite of features designed for efficient data processing and task automation. It provides high precision in extracting information and strong conversational capabilities, crucial for developing chatbots and customer support systems. Its integration with Azure ensures seamless data handling and security, addressing key enterprise requirements. Users can employ its versatile GPT models for diverse applications such as predictive analytics, summarizing large documents, and competitive benchmarking. Despite its strengths, it faces challenges like latency, inadequate regional support, and limited integration of new technologies. Improvements in model fine-tuning and more flexible configuration are desired by users.

What features make Azure OpenAI a reliable choice?

High Precision: Ensures accurate data extraction suitable for critical applications.
Conversational Capabilities: Facilitates the creation of sophisticated chatbots.
Azure Integration: Seamlessly connects with Azure services for enhanced functionality.
Automation Support: Automates repetitive tasks, improving efficiency.
Security Features: Offers robust protection for sensitive data.
Drag-and-Drop Environment: Simplifies user interaction and deployment.

What benefits and ROI should users consider?

Natural Language Processing: Provides superior language model performance.
Quick Implementation: Reduces time to deploy applications.
Scalability: Supports growing business needs with ease.
Versatile GPT Models: Applicable across different industry workflows.

Azure OpenAI is implemented across industries like healthcare, finance, and education for tasks like invoice processing, digitalizing records, and language translation. It enhances policy management, document assimilation, and customer support with predictive analytics and keyword extraction. Organizations in such sectors benefit from streamlined workflows and task automation.