A leading Agtech company sought to integrate a computer vision-based plague detector and classifier into their mobile app, catered for large crops like soy, corn, and coffee. While the application would revolutionize pest management in agriculture, it brought significant challenges. The company needed a solution that would not only accurately detect and classify various pests but also require consistent updates to ensure the model stays precise and effective. They also sought comprehensive technical training for their team to understand and manage the solution and, in turn, create their machine learning-based solutions.
candido.ai engineered a solution using AWS Sagemaker and designed a highly efficient computer vision-based plague detector and classifier. This solution successfully integrated with the Agtech company's mobile app, enabling real-time pest detection and classification. candido.ai didn't stop at the solution implementation, as we also provided exhaustive technical training for the Agtech company's team. This training equipped the team with the knowledge and skills to manage the solution, including routine updates, precision metric checks, and advanced model monitoring techniques. By doing so, they empowered the team to understand and address future machine learning-based solutions independently.
The partnership with candido.ai culminated in successfully integrating a sophisticated plague detector into the Agtech company's mobile app. This development revolutionized the company's pest management capabilities, increasing effectiveness and efficiency. Moreover, the training equipped the Agtech team to manage and update the model, ensuring it remained precise and relevant over time. Beyond that, the training proved instrumental in inspiring the team to develop their machine learning-based solutions. As a result, the company was not only transformed in how it handled pest control but also in its internal approach to problem-solving and innovation in a broader sense.