When you convert your idea into words in our POC Template, you’re reviewing your entire concept and finding issues that you wouldn’t uncover otherwise. This process also helps you slow down your thoughts and think more clearly about what needs to be done.
This is ultimately the most valuable benefit out of a POC. The feedback you will gather will help fine-tune your idea. It will also help you understand if you found a gem.
A POC helps you save money in two ways:
To be successful, a computer vision project should have a clear business goal and benefit. We are able to describe the goal and benefit in one to two sentences, in order to set a clear crystal mindset for everyone.
The goal here is to translate the business outcome into simple success criteria that can be used to measure the effectiveness of the solution.
We identify the right techniques up front will clarify the data requirements and enable our team to focus during the execution phase.
If the scenario is not focused on one of our more than +30 pre-trained models ready to use, we will need to collect and label data to train a new model.
Once we have a good set of images labeled we are ready to shift to model training. In transfer learning, a pre-trained model is repurposed for a new scenario.
With the model deployed, we are ready to interact with the new model in a real-world environment. At this point, we start to solicit feedback. Developing a machine learning model is an iterative process of trial and error. If the model is not performing well, there are many steps we can take to improve performance.
The gathered feedback lets us verify the usability and feasibility of the solution. It also informs of any needed improvements to the proposed product and gives significant insight for other relevant actions moving forward.
A Proof of Concept (POC) allows for the testing and validation of the computer vision project. This helps to identify any potential issues that may arise and ensures that the project is feasible.
POC helps to streamline the development process and reduce development time. This is because any problems are identified early on and can be addressed, ensuring that the project is completed within the desired timeframe.
A POC provides a demonstration of the value of the project to stakeholders and helps to secure funding and support. This is because it provides tangible evidence of the potential benefits of the project.
POC minimizes the risks associated with computer vision projects. This is because problems are identified early on and can be addressed, reducing the chances of the project failing.
The Computer Vision Proof of Concept (PoC) provides profitability by allowing companies to evaluate the value and potential of this technology before investing on a large scale, minimizing risks and optimizing resources based on the results obtained in the testing phase.
