When you manage the development of an application or web service, one of the key questions to ask yourself is: should you use an open API or a closed one? This question becomes indispensable at the beginning of development work and as you plan the mission you want to achieve. So, let’s discover the difference between these APIs.
Open API vs. Closed API
OPEN API
An open API, also commonly known as a public API, is an essential part of the technology infrastructure. These interfaces provide entry to the functionalities and data of AI applications without requiring access to their source code. Thus, open APIs are available to anyone who wants to use them. In addition, they offer not only access to publicly available information but also the ability to interact with applications at different levels.
Open APIs act as a gateway. They allow developers to communicate and collaborate with applications directly by calling specific functions or accessing data. This allows developers to:
- Build their applications
- Extend existing functionality
- Create integrations to enhance the capabilities of AI applications
Open APIs allow different entities to create and maintain their own tools while retaining the ability to integrate with other applications. This is particularly important in the field of AI, where the diversity of tools and data is key to achieving application effectiveness and scale.
Examples of open APIs in AI applications include:
- Google Cloud Vision API: Provides image analysis functions such as object recognition, labeling, and image classification.
- OpenAI’s GPT API: Provides access to advanced language models, such as GPT-3, for text generation, question answering, and many other applications.
CLOSED API
A closed API is a private, proprietary tool that restricts access to the application’s features through a license agreement. The application’s source code is not publicly available, allowing the owner to retain control over the product and user experience.
In the case of closed APIs, access to application functions is limited to the company’s internal development team. It allows control over the types of applications that can be developed. The application owner fully controls which features to use and how to develop the application. We suggest reaching out to an AI consulting company for expert guidance in determining the optimal solution tailored to your requirements.
Here are examples of closed APIs in AI applications:
- Microsoft Azure Cognitive Services: offers several advanced AI services, such as speech recognition, text analysis, and facial recognition. However, some of these services are only available to customers who have Microsoft Azure cloud accounts and use paid service plans.
- Amazon Comprehend Medical: This is a medical text analysis service that helps identify medical information in documents. However, access to this service is limited to customers who use the AWS platform and have the appropriate access privileges.
Let’s summarize:
| Open API | Closed API | |
| Availability | Available to all interested users | Limited access, usually to in-house or paying customers |
| Source code | Publicly available | Restricted, non-public |
| Access control | Restricted, usually without authorization | Strict access control requires authorization |
| Flexibility | Flexible, capable of creating a variety of integrations | Limited, with control over the type of applications that can be created |
| Use cases | Often used in open, innovative projects | Appropriate in cases where there is a need for confidentiality and control |
| Service availability | A wider range of services and features available to the public | Some advanced services and features may be available only to selected customers |
| Innovations | Foster innovation through an open environment and collaboration | Limit innovation through control and access restrictions |
Open API in AI applications
CHATBOTS AND VIRTUAL ASSISTANTS
Developers use open APIs in applications to build chatbots and virtual assistants. With them, various AI technologies can be integrated, such as NLP, response generation, user mood analysis, external data sources, etc.
ML PLATFORMS
Platforms offering tools to create and train ML models provide open APIs. It allows developers to build, train, and deploy models directly from other applications.
SOCIAL MEDIA SENTIMENT ANALYSIS
Open APIs are used to analyze sentiment in social media posts. This allows you to monitor and analyze user opinions on products, brands, events, etc. Moreover, APIs enable integration with social media platforms or CRM systems.
Closed API in AI applications
SECURITY
In the field of cybersecurity, some AI applications offer solutions based on closed APIs. They enable the analysis of user behavior, the detection of attacks, or the identification of threats. These functions might have restricted access.
HEALTHCARE
In the healthcare sector, closed APIs are used to analyze medical data, diagnose diseases, monitor patients, etc. These APIs might have limited access.
INTELLIGENT BUSINESS PROCESS AUTOMATION
In business, there are AI applications that offer closed APIs for automating business processes, such as customer service, order management, data analysis, etc. Again, there might be limitations on accessing these APIs.
Conclusion
In conclusion, open and closed APIs have different characteristics and are suitable for different use cases, depending on the needs of the organization and the nature of the project. Open APIs encourage innovation and flexibility, while closed APIs provide control, security, and compliance.