The Nonymous BeKnown MIL- Machine Interconnected Learning

1) The increase in technology has brought many advantages and disadvantages when it comes to job opportunities. One rising problem is that many employees around the world are looking their current jobs for technological displacement, missing an important workforce in the process. 

2) BeKnown MIL is a software project focused on creating an interconnected network to a machine learning system that reorganizes, matches and evaluates data to provide adaptability to working processes and interview applications. Data is not connected, but analysed for a process and takes actions available to the data provided. 

3) As an example, if a person applies to a startup and is rejected for the process, data collected is reorganized and redirected to the opportunities available. If the person lacks the require skills for the process, data is adapted and provides resources available to the required jobs. Information available allows to know the number of jobs globally. 

Currently we are working at the University of Waterloo as students apply to coop jobs and approximately 20% of them do not find opportunities for the lack of experience or others. We are doing an initial proof of concept with them and startups to improve our current demo and create an MVP, so that we can create a better process for people who do not have job opportunities and those with relevant experience to the job board. These processes and activities is expected to improve the job application of around 2.5% of the national population in Canada. As internet and inter connectivity is an increased problem for marginalized communities, the process will improve the speed of identification of qualities for them, so that the use of resources is lower than the current ones. 

We are making primary and secondary research as we continue with the demo and MVP. We work as support of talent and experience, based on culture, economical background and academic experience. The virtual space creates a process that interacts with unemployed populations by evaluating their interview activities and provide resources. These resources can be academic institutions, virtual knowledge and validation of information for new talent based on the information available for the process.

We are creating a virtual space interconnected with organizations and startups available. Startups uses the space to identify data available and interview applications of other organization for different compensations or criteria decided by the institutions. The process is significantly new, and helps startups to find talent faster and reduce the number of applicants faster. 

 For more information of the project and process concept you can read the following document: https://docs.google.com/docume...

We use data in an interconnected network and machine learning to provide a process of actions based on that data. That means that information is not overlap and is not required to be collected, but only evaluated for an action. For example, if a person does not have experience, it creates a process exclusive for this kind of person, and creates only the actions for that data. Data is protected and used by institutions, so companies and startups can use information as desired. 

The idea aims to connect a new network to understand the real numbers of employment, and requirements of talent. Current, the statistics only show perspectives of jobs, but it is different if you know how many jobs exist to match all jobs with available workforce. This process also adapts jobs to the current needs of the market, so if many jobs are related to the market, the system says that to the population and creates processes with institutions for better and professional applicants. The process avoids college students to do a career that they will not work.

Right now we have 10 people in our first demo for the implemenattion, the project wants to increase that number to 1000 to 10000 users after the first MPV, and a sustainable number of 10 million to 100 million users in the next five years.

Raising 10k in funds for the MVP 

Connecting with networks and organizations 

Make an initial partnership with the University of Waterloo to work with their system

Find partners to connect 

Find initial users for our MVP

Be accepted in an incubator, more specifically the incubator at the university