With the many additive manufacturing companies going public and the wild west of mergers/acquisitions, the 3D printing industry is exploding faster than ever! With this huge momentum, the need to educate a competent workforce that is trained to use 3D printing technology has never been more desired by employers. Companies are investing in the machines and technology that these additive manufacturing companies are selling, but struggling to find engineers, technicians, sales associates, and management who are familiar with the technology to implement them in their processes effectively. It is time for a solution to come to market that aims to provide the industry with the knowledge and training they need.
Our main competitors are online forums and videos that are scattered, sporadic, and inaccurate. Imagine being a 3D printing engineer trying to learn when you ask “How do I do this?” and the BEST answer they can give you is, “Look it up on the internet”. With our easily accessible online platform that is always updating with unbiased, commercial-focused, gamified education, Minerva will operate where our competition falls short so that we can provide a great experience. Our team also has unique advantages. Our third co-founder is Daniel Hutchinson, the founder and CTO of PostProcess Technologies, which is a world leader in the 3D printing industry. He brings a wealth of resources, industry relations, and experience to Layer Slayers.
With the prize money, Layer Slayers intends to produce educational content to put on the MVP platform that we have. Then we will be able to test the platform with the initial customers that we have lined up who are ready and excited to use Minerva. Our goal is to get into the learning and iteration feedback loop as soon as possible. Once the early adopters are using Minerva, we will gain a better understanding of their needs by running experiments about their experience with the platform and content. Optimizing both the content and platform will be important to our success so this is where we currently want to spend time experimenting. The $10000 will take us far into this iterative process and will allow us to begin this right away.