To address the client's challenge of automating the determination of human organ allocation boundaries from images, we outsourced part of the research to a specialized research institute.
The research, which took three weeks and cost $5,000, helped us discover an approach to solving the problem. Afterwards, we implemented a solution based on neural networks, using Python language and TensorFlow to develop the product.
In response to the client's plan to integrate the solution with other information systems, we designed it as a microservice. On top of this, the client presented us with additional tasks to address.
As a result, we developed multiple microservices tailored to solve various image recognition problems, ensuring seamless integration with any external system.