The Azure OpenAI Service is a Microsoft platform that provides OpenAI's artificial intelligence models (GPT-4, GPT-4o, DALL-E, Whisper) within the Azure infrastructure, with enterprise-grade guarantees of security, privacy and compliance. Company data is not used to train the models and never leaves the customer's Azure infrastructure.
Many companies have tried ChatGPT and seen its potential. But using ChatGPT directly in a business context raises legitimate questions: is the data secure? Does it comply with GDPR? Are the results reliable enough for business decisions? The Azure OpenAI Service answers these questions by offering the same models with additional layers of security, privacy and enterprise control.
What the Azure OpenAI Service is
The Azure OpenAI Service is the enterprise version of OpenAI's models, hosted on Microsoft's cloud infrastructure. It offers:
- Access to the latest models: GPT-4, GPT-4o, embeddings, DALL-E (image generation), Whisper (audio transcription).
- Data isolation: the data submitted is not used to train models and is not accessible to other customers.
- Integration with the Azure ecosystem: databases, storage, monitoring, identity (Azure AD).
- Enterprise SLAs: availability, support and regulatory compliance guarantees.
- Content filtering: configurable filters to prevent misuse.
Azure OpenAI vs direct ChatGPT
| Criterion | ChatGPT (direct OpenAI) | Azure OpenAI Service |
|---|---|---|
| Data used for training | May be (opt-out available) | Never |
| Data location | OpenAI servers (US) | Azure region of your choice (e.g. Europe) |
| GDPR | Complex to guarantee | Full compliance available |
| Enterprise integration | Limited (generic API) | Native integration with Azure, AD, private networks |
| SLA | No guarantees | 99.9% availability |
| Content filtering | Basic | Configurable per use case |
| Price | Fixed subscription or pay-per-use | Pay-per-use (per token processed) |
Enterprise use cases
- Internal assistants (RAG): chatbots that answer based on the company's own documents (see our article on RAG).
- Document generation: sales proposals, reports, emails, based on templates and CRM data.
- Text analysis: email classification, information extraction from contracts, sentiment analysis of customer feedback.
- Translation and localisation: translation of technical documents, manuals, communication with international customers.
- Summarisation: meeting summaries (from transcripts), summaries of long reports, executive briefings.
How much it costs
Azure OpenAI operates on a pay-per-use model based on tokens processed (input + output). Indicative costs:
| Model | Cost per 1M tokens (input) | Cost per 1M tokens (output) |
|---|---|---|
| GPT-4o | 2.50 USD | 10.00 USD |
| GPT-4o mini | 0.15 USD | 0.60 USD |
| GPT-4 | 30.00 USD | 60.00 USD |
For most enterprise applications (chatbot, document analysis, email generation), the monthly cost ranges between 100 and 800 euros, depending on usage volume. The GPT-4o mini model offers an excellent balance of cost and quality for many use cases.
Security and GDPR
- Data is not used to train models. Microsoft and OpenAI do not access Azure OpenAI customer data for training purposes.
- Data processed in the chosen region. You can select data centres in Europe (West Europe, North Europe) for GDPR compliance.
- Integration with Azure Active Directory. Access control by user, group and permission.
- Private networks. The service can be configured within a private virtual network, with no public access.
- Logs and auditing. All access and usage is logged for auditing purposes.
How to get started
- Define the use case. Start with a concrete, measurable case (e.g. internal assistant, document processing).
- Provision the service. Create the Azure OpenAI resource in the Azure portal, in the desired region.
- Develop the prototype. Test using Azure OpenAI Studio or via the API.
- Integrate with company data. Use RAG to give the model context from the company's documents.
- Test and validate. With real users, measure quality and adjust.
- Move to production. With monitoring, content filtering and cost management.
At Engibots, we help companies implement Azure OpenAI solutions integrated with their data and systems, ensuring AI runs securely, on European infrastructure and in compliance with GDPR.