AI-as-a-service (AIaaS) for Developers: Building Intelligent Apps Without a Data Science Team

Artificial Intelligence development is being adopted widely and executed in several industries. Developing AI models from the beginning is not only expensive but also consumes a lot of time. This is the reason several businesses are opting for artificial intelligence or AI as a service partnership with renowned third-party service providers. It assists organizations in personalizing the existing solutions so that it suits their requirements. The AI applications are easily measurable and are a good option for small, medium and big businesses.

Let’s learn more about AI as a service and how an AI product development company helps businesses in the seamless integration of artificial intelligence in their internal processes.

Different kinds of AIaas

AI as a service helps businesses in decreasing the risk of making investments in novel technology. Organizations can also start small and increase as per their budgets. In addition, they can also do experiments and try various applications, cloud platforms etc. to find the right combination. For instance, a third-party AIaas provider that is a certified partner of Google, AWS and Azure can assist a business in selecting the best cloud solution for their requirements.

Furthermore, recent AI technology needs supportive hardware such as GPUs, APIs etc. The elements are well taken care of by the provider of AIaas so that the apps run on remote cloud platforms and businesses can easily save resources for important operations.

Types of AI-as-a-service

Here are some of the major kinds of AI as a service provided by AI product development companies:

Digital assistants and bots

Chatbots and assistance are one of the common kinds of AIaas provided by service providers. These bots are developed by making use of AI, ML and NLP technologies for understanding human input and providing customized output. They are utilized in consumer service departments to decrease pressure on the executives and offer 24*7*365 days of support to the consumers. In the same way, digital assistance is utilized for setting up self-servicing solutions for the employees so that they can rapidly access the information they require or troubleshoot the device whenever required.

Machine learning frameworks

Developers make use of the ML frameworks for building AI models for various purposes. The frameworks offer the basic foundation and can be mixed with third-party applications. However, the process of building an ML data pipeline is complicated and needs domain expertise. Businesses can select AIaas as a part of AI/ML development services for accessing ML models as well as frameworks relevant to their processes. The models are well used on the cloud servers of the provider and save computing resources for the whole enterprise.

APIs

It is an application programming interface that helps in connecting two or more software for enhanced functionality. In general, businesses make use of AIaas APis for NLP abilities which assist in the analysis of sentiment, knowledge mapping, data extraction etc. In the same manner, computer vision assists in extracting elements from the images and videos to help the building applications for face recognition, ID verification etc. APIs also facilitate various software in consistently sharing data and delivering the outcome to the end user.

AI as a service benefit for developers

AIAaS offers developers the required tools and framework for integrating AI into applications without needing to develop AI models from the beginning. Here are a few ways by which AIaas benefits the developers:

Decreased complications

AIaas extracts the maximum complexity involved in AI and ML. Developers do not have to worry about developing and training machine learning models, managing the infrastructure or dealing with complicated algorithms. Rather they can make use of the ready-to-use AI models and services, thereby speeding up the development and decreasing the learning curve for executing AI features.

Fast time for marketing

With AIaas developers focusing on developing applications and services instead of spending time on developing AI models from the beginning. This facilitates rapid prototyping and testing, resulting in a fast time for the market for AI-driven solutions. Developers can execute features such as face recognition, natural language processing along with predictive analysis by incorporating pre-trained AI models.

Measurability

AIaaS platforms specifically run on cloud infrastructure, providing automatic measurability. When applications grow and need more computation power, the AIaaS provider manages to measure the AI workload. This means that developers do not have to worry about the provisioning of extra resources or management of servers, thereby making it easy to scale up the AI apps to manage enhanced demand.

Cost-effectiveness

Developing custom AI models and maintenance of the infrastructure for machine learning is not cost-effective and is resource-intensive. With AIaaS, developers can access AI technologies at a fraction of the cost with models such as pay-as-you-go. This decreases the barrier to entry, mainly for small development teams that want to use AI without the burden of in-house development.

Easy access to the latest AI abilities

AIaaS platforms provide a wide range of the latest AI functionalities like computer vision, speech recognition and many more. Developers can incorporate these abilities into their applications by making use of APIs, even though they do not have the required expertise in machine learning.

Conclusion

Thus, to summarize, AI-as-a-service helps developers in simplification of AI integration, decreasing costs, enhancing measurability and offering access to AI functionalities. Developers can emphasize developing innovative applications, using the power of AI without worrying about the management of complicated AI infrastructures.