AI in AI

Artificial Intelligence in Application Integration

In the evolving landscape of technology, implementing artificial intelligence (AI) into application integration solutions is becoming more common. This blog post explores how the OpenAI API can be used within Dovetail, with a focus on its functionalities, benefits and use cases.

OpenAI API in Dovetail

To interact with the OpenAI API, you need to authenticate your requests with an API key, which is obtained by signing up for an account on the OpenAI platform. This key is included in the header of your requests to ensure secure and authorised access. Depending on the model you want to use you also have to add credit to your balance.

The OpenAI API allows for the customization of responses through role-based messages. You can send messages with roles to guide the AI’s behaviour and context. The system role defines the behaviour or persona of the AI, while the user role represents the input or query.

For example, the following API request body:

    "model": "gpt-4",
    "messages": [
            "role": "system",
            "content": "Return Alpha-2 ISO codes for countries."
            "role": "user",
            "content": "Netherlands"


Returns this response body* from the API:

    "message": {
        "role": "assistant",
        "content": "NL"


* For clarity the meta data is removed from the response. It contains data like the request id, timestamp, usage information, etc. etc.

In the example above we are telling the AI we expect it to return Alpha-2 ISO codes for countries we are sending to it. The user role prompts a country that we want the AI to find the ISO code for. After sending this request it responds with NL, the ISO code for the Netherlands. The data in this response can be used within your flow immediately.

The concept of assistants in the OpenAI API refers to reusable request templates that streamline common tasks. You can configure an assistant for the country ISO code defining the system role functionality and then interact with this assistant directly. This can significantly reduce development time and ensure consistency in API interactions.

Benefits of using AI in Dovetail

By implementing OpenAI into your Dovetail flows, businesses can significantly enhance their operational efficiency, provide better customer experiences and automate a wide range of tasks, all while maintaining high data accuracy and consistency. Integrating these AI capabilities into your existing flows opens up numerous possibilities for enhancing and automating various business processes. Here are some use cases:

Data enrichment, conversion and translation

Natural language processing

Error handling optimisation

Risk assessment

Cost comparison

Using the OpenAI API is cost-effective compared to manual data entry. API calls to language models often cost less than or only a matter of cents per request, depending on the complexity of the task. Manual input requires significant human resources, which translates to higher labour costs and error rates.

AI can process vast amounts of data swiftly, around the clock and accurately. This reduces operational costs, while decreasing processing time, increasing the availability of your services and reducing the costs of mistakes.


Enhance your flows with the power of OpenAI almost effortlessly within Dovetail, fully in line with our premise ‘Integration made Easy’. By leveraging AI, businesses can significantly enhance efficiency, reduce costs, improve service availability and maintain high data accuracy. Embracing AI in application integration not only keeps your business competitive but also prepares you for future technological advancements.

Dovetail iPaaS

An iPaaS is an excellent way to support your application integration. iPaaS is short for integration Platform as a Service. Dovetail is such a Platform.

The Dovetail application is a no code, easy to use integration tool that can connect almost anything.

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