Funding Source: Machine Learning (ML)

Problem: With COVID-19 still at large, established business practices are changing. Touchless or contactless systems offer a new level of convenience and ease of use while also addressing pathogen and virus transmission issues at access points. It wasn’t that long ago people didn’t think twice about touching elevator buttons, door handles, and check-in kiosks on their way in and out of work, now, touching these communal surfaces has become a point concerns over employee health and safety issues._x000D_
_x000D_
Solution: Spintly uses IoT as the primary enabler for the access control platform. The company uses the Bluetooth signal from the employee’s device to form an IoT mesh network of devices to send data to the cloud. The key part of the network is the Spintly Mesh gateway. This gateway connects to the IoT Network of employees on one side and connects to the cloud system on the other side for providing access.

Problem: Companies or organizations need to verify the background of the blue-collar workers with the right skill set for the job and manage these workers hired in bulk.

A need for a platform was felt that could provide the essential details and a background check on behalf of the companies that want to hire blue collar job workers and then manage their working as well as help these workers find a suitable job for themselves. Need was also felt to provide additional services needed by this group like training, upskilling, telemedicine etc.

Solution: The solution is reliant on deep-learning algorithms. It uses facial recognition technology. By using the data generated on employees, such as willingness to learn or family structure, it determines ratings of employees.

Problem: A lot of companies needed employees for a certain period but did not have the manpower or incentive to do it in-house. The companies also required gamut of services, ranging from temporary staffing to payroll process outsourcing, regulatory compliance services and training and assessments.

Need was felt to come up with a solution which will provide all these companies with good, credible workforce by picking eligible candidates from a variety of sources. AI and ML was used to scans resumes match the profile or interests with the vacancy.

Solution: Workers can check, search and apply for jobs in their local languages. The interview process is based on the answers provided by the candidate to questions framed around the candidate‚ CV using AI/ML based tools. Open-ended questions are matched with previously fed data and close-ended questions are used for elimination.

Problem: In today‚ HR industry, the recruiters are juggling tons of resumes, complicated hiring routines and time-consuming processes. On the other hand, job-seekers are subjected to lengthy hiring procedures.

The objective is to introduce a platform that can bridge this gap between the recruiters and job seekers. A solution that matches the right talent to the right opportunity , accelerates the hiring process by reinventing the way one attracts, shortlists, and engages candidates/

Solution: Vasitum, the developer of this solution, leverages AI from the top of the hiring funnel through to the moment of hire. From the start of the process, the AI-based chatbot ‚Ai Vasi sources ideal profiles for the job, stack ranks, and pre-screens them for the role. Scanning through numerous CVs using keywords, prioritizing, and segregating them accordingly is based on an AI-powered Applicant Tracking system.

Problem: The COVID pandemic has taken a toll on the jobs of many employees. Research revealed that out of the 100 million working population in India that earns regular salaries, 80% of the people run out of money between pay-checks. It is also difficult to get help from friends, family and even other employers due to the unfortunate pandemic._x000D_
_x000D_
Solution: The ML-based rules engine works 24√ó7 for continuously monitoring risk profiles of the existing customers. The scorecard formulas are updated at a regular interval by using the recommendations generated by the self-learning credit approval engines which is then verified using machine learning algorithms for approval of getting an advance salary.