SimYIn is a small start-up company based in Santa Cruz, CA. We're building a platform to make intelligent data analysis and machine learning accessible to those with no technical expertise. Think of us as doing for AI and machine learning what SQL did for databases.

We've built a platform to make intelligent data analysis and machine learning accessible to those with no technical expertise. We’ve successfully tested the platform in the network intrusion detection and stock market analysis domains.

Presently, we are working on using the platform to create a software solution that would allow users to obtain concise summaries of issues being discussed in the online community about a particular product. What makes SimYIn special is the combination of the novelty of our technology, team expertise and the vast potential for monetization. Machine Learning (ML) has been around for a long time in the academic domain, but even today it lacks commercial viability and usability. Only recently have organizations made use of ML in day­to­day applications such as video and music recommendation and targeted advertisement. However, ML applications are under­used and lack widespread commercial viability.

The development of ML applications requires ML experts and domain experts to work together. All of us have domain expertise in our respective domain ­ if we want a specific type of smartphone, we are the experts of the domain of smart phones that fit our needs. The problem we face is that we don’t know how to build a ML solution that is capable of automatically finding us the smart phone that best fits our criteria, since not all of us are ML experts. Additionally ML experts cannot tailor their solutions to each individual’s criteria, since they are not domain experts in our domains.

This is where SimYIn steps in. We’ve built a framework that makes it easy for people unfamiliar with ML to harness the power of ML. We are scraping the internet to collect any information that is related to the product of interest to the user. We then apply semantic analysis on the collected data and store it in a format that makes it easy to plug into our platform that brings the power of ML to non­ML users. This allows people to obtain information relevant to specific questions.

Our product is very attractive from monetization standpoint, because it lends itself to several possible monetization channels. It can be licensed to companies, so that they can use our system to learn of critical issues associated with their products after launch. Companies can also use our product to analyze and learn more about their direct competitors. At the individual level, we can bundle our product in smartphone apps, which can be sold through the app marketplace.