Submitted

Last Updated June 19, 2017

Youth, Skills, & the Workforce of the Future

CLERK

Team Leader

Massa Baali

Step 2

Our Solution

CLERK

Our solution's stage of development:

Pre-Seed

Our solution:

CLERK is an intelligent recruiting tool that discovers applicant's skills using machine learning algorithms that relies on multiple features based on the recruiter's requirements. CLERK filters top applicants among a large pool of candidates by one click!

Our pitch:

https://drive.google.com/file/d/0B_wJg3n8DYt_eVg0b3U1djNfS3c/view?usp=drivesdk

The problem:

According to WSJ 30% of the people worldwide are not comfortable with their jobs. Organizations are wasting time, money and efforts to recruit a person. As Einstein said everybody is a genius but if you judge a fish by its ability to climb the tree it will live it's whole life thinking its stupid. For that CLERK will put the right person in the right position and discover applicant's skills and personality type to find if he fits the position.

Why our solution will solve the problem:

Firstly since youth hugest problem is finding the right job especially after graduating from college or during their university life and they don't know what are the skills they have or they should have they don't know that they should focus on their strengths rather than focusing on weaknesses. They don't know if their personality type matches a specific job. CLERK would be the solution!.

Who recommended you to Solve - or - how did you find Solve?

Media

Step 3

Our target outcomes:

We will end up with a better workplace for everyone.

Both recruiters and people who are seeking a job.

Platform.

How we will measure our progress:

Check if both sides are happy with the system! - 3 early adopters, 100 tested applicants.

The populations we will benefit initially:

Adult
Upper middle income economies (between $3976 and $12275 GNI)
Bachelors
Masters
Non-binary

The regions we will benefit initially:

Europe and Central Asia
Middle East and North Africa
US and Canada

Step 4

The technologies we employ:

Digital systems (machine learning, control systems, big data)

Why our solution is unique:

We are using advanced machine learning algorithms to classify skills and personality types using NLP in order to track applicants words.

Why our solution is human-centered:

Since this tool helps recruiters in making recruiting process easier. It helps the communities by putting the right person in the right position.

How people will access our solution:

By using web application.

Technology-Readiness Level:

4-5 (Prototyping)

Our website

http://www.clerk.co.com

Step 5

Our organization:

For-Profit

How we will sustain our team financially:

Now we are seeking for a grant. Then we would do testing on many companies. Then we will offer it to the companies and we will get subscriptions from them.

The factors limiting our success:

Since the idea is new it would be hard to create a culture for the companies to accept it.

How long we have been working on our solution:

1 year

How long it will take to develop a pilot:

3-6 months

How long it will take to scale beyond our pilot:

6-12 months

Our expected annual budget:

50000

How much of our budget we've secured to date:

Step 6

We're looking for partners in these fields:

Technology Access
Human+Machine
Future of Work

Why we're applying to Solve:

Getting a feedback about the startup. To get connected with a large network. To make a positive impact in the community here and in the place I would go to as I always aim to.

Our current partners:

No partners.

Who are your competitors?

Indirect LinkedIn

Direct recruiting agencies

Solution Team:

Massa Baali