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Introduction
JobMinglr, developed by Xicom in partnership with its visionary founder John Carter and headquartered in Austin, Texas, is a cutting-edge job-matching platform engineered to revolutionize how job seekers and employers connect. By leveraging advanced AI algorithms and machine learning, the app delivers hyper-personalized job recommendations based on users’ skills, experience, and preferences. Available on both Android and iOS, JobMinglr dramatically shortens the recruitment cycle, reduces mismatches, and boosts hiring efficiency. With its sleek UI and data-driven backend, JobMinglr turns the traditionally tedious recruitment process into a streamlined, productive experience for both candidates and recruiters alike.
Project Name
JobMinglr
Category
Job Search/Recruitment
Location
USA
Services Offered
Design & Development
Industry
Recruitment Industry
Technologies
React Native, Node.js, Machine Learning
Client needed a platform simplifying job search and hiring with personalized recommendations based on profiles, preferences, and real-time data.
Transforming the recruitment process with JobMinglr's intelligent job-matching algorithm.
The client needed an efficient and intelligent platform that not only simplified the job search process for candidates but also optimized the recruitment journey for employers. The objective was to create a feature-rich mobile application boasting the smart job matching algorithms that analyze profiles, skill sets, past experiences, and user behavior to generate highly relevant recommendations. The platform had to support real-time updates, push notifications, easy application tracking, and profile management. It also needed a robust backend to support admin functionalities, data analytics, and scalability for future enhancements. Additionally, the client emphasized a user-friendly interface that maintained engagement and usability across different devices and user types.
With the competitive nature of the job market in mind, the solution had to offer a seamless and proactive hiring experience, reducing manual efforts, eliminating mismatches, and ensuring timely and meaningful connections between job seekers and employers.
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Book Free ConsultationProject Challenges
The client encountered multiple challenges in creating a truly efficient and personalized job-matching platform. Existing solutions in the market lacked the intelligence to match users accurately, which resulted in irrelevant job suggestions, poor user engagement, and delayed hiring processes. Additionally, limitations in filtering, UI complexity, and system scalability hampered both candidate and employer experiences. Therefore, here they need to create a smarter, more intuitive solution.
- Difficulty in offering personalized job matches for job seekers is affecting job relevance.
- Limited filtering and search functionalities for employers to identify qualified candidates quickly.
- Inefficient application processes led to longer recruitment cycles.
- Inaccurate candidate-job matching causes higher rejection rates and lower placement success.
- Low user retention and engagement due to irrelevant job listings.
- Lack of real-time job application tracking and notification systems.
Our Solution
Xicom developed JobMinglr, a feature rich job matching app using machine learning to match job seekers with employers based on comprehensive profiles and requirements.
Xicom, being a leading AI development company, has provided a robust job-matching app that utilizes machine learning to recommend personalized job opportunities to seekers while offering employers tailored candidate profiles.
Using this solution, job seekers can create and customize their profiles, upload resumes, and receive real-time job alerts based on their skills and preferences. Employers can post job listings, filter applicants based on skills, and track the status of their job postings and candidate applications in real time. We created an app with an intuitive design that ensures a seamless user experience, while its scalability supports future growth, making it a long-term solution for job matchmaking.
Key features developed by Xicom along with the customized solution.
Admin Panel
- User management (for both job seekers and employers).
- Job posting and candidate management.
- Job posting approval workflows and job analytics.
- Reporting features for performance tracking and insights.
Job Seeker Panel
- Personalized job recommendations powered by machine learning.
- User profile customization (skills, experience, preferences).
- Real-time job alerts and notifications.
- Resume builder and job application functionality.
Employer Panel
- Job posting with customizable filters for candidate matching.
- Real-time notifications of new job applicants.
- Detailed candidate profiles for efficient filtering.
- Interview scheduling and in-app communication tools.
JobMinglr drastically enhanced the job search and hiring process for both job seekers and employers by making it fast, reliable and efficient.
Book Free Consultation01
40% increase in job seeker engagement due to personalized recommendations.
02
With our app, 35% reduction in time-to-hire for employers.
03
Our app leads to a 45% improvement in job matching accuracy and ensures better job placements.
04
There is a 30% growth in active users within the first quarter of the app launch.
05
25% increase in successful job placements via the platform.
06
50% improvement in app usability, leading to higher retention rates.
Our agile app development process and strategy for JobMinglr.
Our team has adopted an agile approach to create JobMinglr, considering continuous feedback loops and regular updates. This iterative process enabled the team to adapt quickly to new challenges and incorporate user feedback at every stage. The agile methodology allowed for rapid prototyping, timely feature releases, and a product that aligned with the client's objectives.
Strategize and Planning
We conducted in-depth discovery sessions with the client to understand their goals, user personas, and pain points in the current recruitment solutions.
Develop And Automate
Using agile sprints, our development team built core modules for matchmaking algorithms, job filtering, user profiles, and notifications.
Optimize and Simplify
Post MVP launch, real user feedback was analyzed to simplify the UI/UX, improve job relevance through AI-driven suggestions, and fine-tune the onboarding process.
Sustain and Scale
After successful deployment, we focused on scalability and maintenance, integrating cloud-based solutions for data handling and expanding capabilities.
"Xicom truly exceeded our expectations. Their expertise in AI and mobile development helped us build a powerful, intuitive job-matching platform. The team's responsiveness and innovation made all the difference. We’ve seen a significant boost in user engagement and placement success. Couldn’t have asked for a better tech partner. From the first discovery session to post-launch support, their commitment to quality and user experience stood out. Thanks to Xicom, JobMinglr is now a game-changer in the recruitment space.
John Carter
Founder and CEO JobMinglr
