Artificial intelligence

Best Practices and Tips for Developing AI Applications and Solutions

Artificial intelligence (AI) is transforming the world in unprecedented ways. From healthcare to education, from entertainment to finance, AI is enabling new possibilities and opportunities for businesses and individuals alike. However, developing AI applications and solutions is not a trivial task. It requires careful planning, design, implementation, testing, and deployment, as well as ethical and legal considerations. In this article, we will share some best practices and tips for developing AI applications and solutions, based on our experience and research. 

Define the problem and the goal 

The first step in developing any AI application or solution is to define the problem and the goal. What is the main challenge or opportunity that you want to address with AI? What are the expected outcomes and benefits of your AI solution? How will you measure the success and impact of your AI solution? These questions will help you to clarify the scope and purpose of your AI project, as well as to identify the key stakeholders and users involved. 

Choose the right data and methods 

The next step is to choose the right data and methods for your AI solution. Data is the fuel of AI, and the quality and quantity of your data will determine the performance and accuracy of your AI solution. Therefore, you need to collect, clean, label, and analyze your data carefully, and ensure that it is relevant, representative, and unbiased for your problem and goal. You also need to choose the appropriate AI methods and techniques for your data and problem, such as machine learning, deep learning, natural language processing, computer vision, etc. You should consider the trade-offs between complexity, scalability, interpretability, and explainability of your AI methods, and select the ones that best suit your needs and expectations. 

Test and validate your AI solution 

The third step is to test and validate your AI solution before deploying it to the real world. Testing and validation are essential to ensure that your AI solution works as intended and that it meets the quality and performance standards that you have set. You should test your AI solution on different scenarios and cases and compare the results with the expected outcomes and benchmarks. You should also validate your AI solution with the feedback and input of your stakeholders and users, and make sure that they are satisfied and comfortable with your AI solution. Moreover, you should evaluate your AI solution in terms of its ethical and legal implications and ensure that it respects the values and rights of your stakeholders and users, as well as the society at large.  

Deploy and monitor your AI solution 

The final step is to deploy and monitor your AI solution in the real world. Deployment and monitoring are crucial to ensure that your AI solution delivers the desired results and benefits and that it adapts to the changing conditions and needs of your stakeholders and users. You should deploy your AI solution securely and reliably and provide adequate support and maintenance for your AI solution. You should also monitor your AI solution regularly and collect and analyze the data and feedback from your AI solution. You should use this information to improve and optimize your AI solution and to identify and address any issues or challenges that may arise. 

A case study: Global Triangles 

Global Triangles, a leading nearshore IT staff augmentation firm, exemplifies best practices in AI application development through a recent success story. In tackling a client’s challenge, the first step was a meticulous definition of the problem and the overarching goal. Recognizing the need to streamline the review process of tens of thousands of reports monthly, Global Triangles aimed to cut time significantly while enhancing accuracy to elevate customer satisfaction and reduce costs substantially. 

Choosing the right data and methods was crucial in crafting a solution tailored to the client’s needs. The team of skilled Global Triangles software engineers leveraged advanced AI algorithms to efficiently analyze and categorize the extensive report data, thereby slashing the time required for the mundane task by over 90%. This not only exemplifies the company’s commitment to employing cutting-edge methods but also showcases the strategic selection of data and techniques to achieve optimal results. 

Following the development phase, rigorous testing and validation were conducted to ensure the AI solution’s reliability and effectiveness. Once proven successful, the deployment marked a transformative milestone. The implemented AI solution not only expedited the review process but also significantly elevated the accuracy, resulting in heightened customer satisfaction. This success story underscores Global Triangles’ prowess in AI application development and serves as a beacon for others looking to navigate the intricate landscape of designing and deploying AI solutions. 

Garry Lea, the CEO of Global Triangles, shared his opinion on the topic of developing AI applications and solutions saying “Global Triangles believes in the power of strategic innovation. Our recent success in deploying an AI solution, reducing task time by over 90%, and enhancing accuracy underscores our commitment to defining problems, choosing the right methods, and delivering transformative results. We envision a future where AI not only streamlines operations but becomes a driving force for sustainable growth and client satisfaction.” 

As Keeley Crockett, Edwin Colyer, Luciano Gerber, and Annabel Latham wrote in their article: 

“From a business perspective, there is a clear relationship between perceived risk in an AI system in a given context and how much trust users have in the decisions it makes” 

This means that developing AI applications and solutions is not only a technical and scientific endeavor, but also a social and human one. Therefore, we need to develop AI applications and solutions that are not only aligned with our goals and objectives, but also with our values and principles. 


In this article, we have shared some best practices and tips for developing AI applications and solutions, based on our experience and research. We hope that these best practices and tips will help you to develop AI applications and solutions that are successful and impactful, as well as ethical and responsible. We also hope that you will enjoy and appreciate the amazing potential and opportunities that AI offers, and that you will use AI to make the world a better place.

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