A mature ecosystem
A stable API, comprehensive documentation, official SDKs for the main languages and a large community. Common problems have known solutions, which speeds up integration.
AI integration · OpenAI
OpenAI API Development: From Business Use Case to Production
Etixio builds AI solutions with the OpenAI API: assistants, information extraction, document search, agents and automation. We build the connections, evaluations and controls that make a model useful in your software, all the way to go-live and ongoing maintenance of the service.
Understanding the technology
A model integrated into your application.
The OpenAI APIs provide access to models that can be integrated into a product or a processing pipeline. The application must organize their context, the tools they can access and the expected formats. Etixio develops this integration to connect a model capability to a use case and business rules.
Calling the model is only a small part of the work. The rest is software: data preparation, access rights, output checks, interface, monitoring and cost control. That is what we deliver, whether it is an AI feature in your product or an AI agent connected to your tools.
The strengths for your product
Why choose the OpenAI API?
OpenAI is the most widely used platform and often the first choice for general-purpose use. We choose it when its strengths match the need, after comparing it on your own examples.
A broad range of models
Reasoning models, lighter models for high volumes, audio transcription, image analysis, image generation and embeddings for semantic search.
Structured outputs and function calling
The model can respond according to an enforced schema and call the functions you expose. This is the foundation of reliable extraction and of agents controlled by the application.
Cost levers
Choosing the model for each step, batch processing, caching and usage tracking help keep costs predictable.
Multilingual use
The models handle French and other major languages, which suits assistants and document processing for international companies.
Our scope of work
Choosing a model family for the work at hand.
We compare GPT families on the same set of representative requests: quality, latency, cost and data processing terms. Access goes through the OpenAI API, or through Azure OpenAI when your organization already runs on Microsoft Azure, with your Entra ID identities and a private network. When sovereignty or on-premises hosting is required, we also compare with Mistral or a self-hosted open-source model.
GPT · Astra
Complex reasoning and development.
GPT · Sol
An option for balancing capability and cost.
GPT · Luna
An option for targeted tasks and high volumes.
Our OpenAI API expertise
The OpenAI ecosystem we work with.
Text and reasoning
GPT models for assistance, summarization, writing and analysis; reasoning models for multi-step tasks.
Data and search
Embeddings and semantic search, search across your documents (RAG), field extraction with structured outputs.
Multimodal
Audio transcription, image and document analysis, image generation when the use case warrants it.
Agents and integration
Function calling, tools connected to your APIs, official SDKs, batch processing, logging and usage tracking.
In the field
An example processing pipeline.
To extract information from a document, we define the expected fields, their formats and the business checks. Results are validated before they feed the target software. Ambiguous cases go through a review workflow. Calls, errors and usage are tracked to measure how the full pipeline performs.
From prototype to production
Taking over a POC built with OpenAI.
Many AI prototypes rely on the OpenAI API: a script, a notebook or a first interface that won people over. We take over the code, instructions and data, then add what is missing for production: authentication and permissions, an evaluation set, error and rate-limit handling, a fallback strategy, logs, monitoring and usage caps.
The service is then maintained and re-evaluated with every model change. See our AI POC to production service, our AI solutions for businesses and our article on the key features of an enterprise AI chatbot.
The choices that matter
Making extraction and calls reliable.
For extraction, structured outputs impose a schema on the model. The application then validates each field and applies business rules before writing to the target software; rejected cases go to a human review queue.
Rate limits and outages are planned for: processing queues, delayed retries, batch processing for non-urgent volumes and a fallback model defined in advance. Each model change is replayed against the evaluation set before deployment.
From work to deliverables
The software delivered around OpenAI.
- Output schemas and validation rules for each extracted field.
- Connections to the data and services within the agreed scope.
- Review queue for ambiguous or rejected cases.
- Evaluation set, error and usage tracking, code and operations documentation.
Depending on your environment, the service calls the OpenAI API directly or goes through Azure OpenAI. The code, API keys and accounts remain yours; the delivery framework specifies environments, access and maintenance.
Frequently asked questions
OpenAI API: your questions.
What is the OpenAI API?
The OpenAI API provides programmatic access to OpenAI’s models (GPT and reasoning models, transcription, images, embeddings). An application sends them instructions and content and receives a response, which can be structured or include function calls. It is one of the most widely used platforms for building AI features.
OpenAI, Claude or Gemini — what are the differences?
OpenAI is often chosen for its versatility and ecosystem; Claude for technical tasks, long documents and agents; Gemini for multimodal use and Google Cloud. We decide on a set of representative examples, comparing quality, latency and cost. If hosting in Europe or on your own servers is required, Mistral or a self-hosted open-source model join the comparison.
Which use cases are a good fit for OpenAI?
Assistants for support or internal teams, writing and summarization, information extraction, document search, transcription, translation and analysis support. OpenAI is well suited to general-purpose and multilingual use.
How do you control OpenAI API costs?
By choosing the right model for each step, reserving the most powerful models for tasks that warrant them, using batch processing and caching, and tracking usage with caps and alerts.
How do you secure OpenAI API calls?
Keys stored and rotated server-side, rate limiting, input validation, data sent reduced to what is necessary, audit logs and permissions enforced by the application. Data processing terms and GDPR compliance are checked for the plan you choose.
What are the OpenAI API’s limitations?
Rate limits, the cost of the most powerful models, latency on complex responses and occasionally inaccurate answers. A production service includes continuous monitoring, a fallback strategy and human validation for sensitive decisions.
How do you monitor a service built on OpenAI?
By tracking call volume, latency, token consumption, error rate and cost, with alerts. We add an evaluation set that is rerun whenever the model or instructions change to check answer quality.
How long does it take to integrate OpenAI?
It depends on the scope: a few weeks for a targeted feature in an existing application, several months for a platform with agents, data and monitoring. A scoping phase sets a realistic initial scope.
Can you take a prototype built on OpenAI to production?
Yes. We first measure the POC on real examples, then add authentication, error handling, evaluations, monitoring and cost tracking. The service is then maintained over time.
What engagement models do you offer?
A fixed-price project for a solution with a defined scope, a dedicated team to evolve an AI-powered product over time, or a targeted engagement (POC takeover, cost optimization, migration).
Let’s build an AI use case integrated into your business.
Tell us what you want to build, the users involved and your technical environment. Together we will define the initial scope to explore.