In the rapid-moving hiring environment, manual work is creating large inefficiencies within the recruitment teams regarding resume screening and candidate shortlisting. To an existing enterprise client based in the USA, dealing with a large volume of thousands of applicant profiles, finding relevant skill match between applications and requirements, and assessing job-fit is a really cumbersome task. Standard ATS solutions often do not support real-time, intelligent scoring of candidates at scale.
The recruitment team asked to innovate to the point of transformation by automation. Therefore, Kkeydos built an enterprise level AI-Powered Recruitment Platform. Based on Node.js, Next.js, MongoDB, and hosted on AWS; this platform utilizes the power of Claude AI to enable real-time parsing of resumes, automated skill extraction, assessment of suitability of candidates, and classification of the applicants intelligently. It features exclusive portals to ensure ease of use by recruiters as well as job seekers.
Kkeydos successfully designed and developed an enterprise-grade HRTech solution and achieved:
80% Reduction in Resume Screening: Top talent are instantly surfaced to recruiters through automatically screened and ranked candidate CVs. Candidate screening time is massively reduced, with the use of a contextual AI Claude engine analyzing unstructured PDF documents.
95% Candidate Skill Extraction & Match Accuracy: The AI-powered engine performs highly accurate matching by evaluating candidate characteristics and comparing it with job requirements.
100% Real-Time Candidate Analytics: Active job pipeline, candidate ranking, skill matching scores and application status, all provided in real-time on a recruiter's dashboard.
99.9% Uptime: Built upon the AWS cloud architecture, it supported numerous concurrent resume uploads while processing requests from the AI API engine with no interruption.
Present-day HR departments and recruitment agencies demand cutting edge recruitment solutions that are able to: analyze large chunks of unstructured data from documents, match candidate profiles against job roles' changing demands.
The client was experiencing: Long resume screening durations:recruiters can only spend few hours per day reviewing unstructured PDF and doc files to spot the best talent;
Manual screening inconsistency: The manual resume screening can lead to missing top talent and slow down the hiring process;
No candidate skill self-assessment: Job candidates are unaware of their match score to a job requisition prior to applying;
Non-holistic candidate tracking: Lack of an integrated candidate journey management solution;
A. Claude AI Integration and Intelligent matching engine
Contextual resume parsing; Linked up ClaudeAI models to automatically extract the details of candidates' contact information, employment history, academic history, and relevant technical competencies.
AI matching score and analysis of compatibility; Devised assessment algorithms to establish a match percentage score based on job specifications and applicant profiles.
AI matching; Placed candidates into a tier order on dashboards for recruiters based on suitability, skill fit, and experience.
B. Fully developed modern web portal (Node.js, Next.js and MongoDB)
Recruitment portal and jobs management; Created intuitive dashboards to list open job positions, specify skill requirements and constraints, review match candidates, and monitor job pipelines.
Candidates' online portal; Allowed candidates to draft detailed profiles, upload CVs, check for suitable matches, and monitor their application progress.
Smart filtering; Introduced fine-grained filters that help recruiters classify candidates based on relevant parameters like skills, level of experience, geographical location, and threshold of AI match score.
C. Enterprise cloud platform architecture and security
AWS cloud based system; Developed adaptable database and server capacities to deal with many concurrent resume submissions, as well as swift, and precise calls to AI services.
Role-based access controls; Defined various levels of user authentications to assure the safety of data and accessibility for candidates and corporate recruits.
Resume Screening. Legacy Setup: Recruiters read several hundred PDF/Word documents of profiles submitted for each job post, 1 by 1.
Kkeydos Custom Engine: Claude AI reads profiles as they are uploaded and matches skills and qualifications in just milliseconds.
Candidate matching and ranking.
Legacy Setup: Shortlisting based on assumptions, a number of human mistakes with slow candidate response time.
Kkeydos Custom Engine: Objectively ranks candidates using a skill matching logic.
Job Seeker’s experience and view.
Legacy Setup: Job seekers submit their profiles without knowing whether their candidates profile matches with the job profile they applied for, or not.
Kkeydos Custom Engine: Applicants can view their compatibility score with the job profile instantly before applying.
Infrastructure and Scaling.
Legacy Setup: Slow databases locally causing slow response at rush hours, data security risks and local hardware infrastructure limitations.
Kkeydos Custom Engine: AWS native infrastructure providing scalable computing environment, data transfer encryption, zero downtime and secure data storage.
We used a standardized engineering process to create the AI recruitment solution:
Discovery & AI prompt Engineering: Designed recruitment workflows, skill-matching logic, and adapted the Claude AI prompts for accurate parsing.
Architecture & schema design: Established a MongoDB document structure, Next.js pages, and safe RESTful APIs.
UI/UX Prototyping: Designed quick, modern user interfaces for the corporate recruiters and the candidates.
Full-Stack & AI Integration: Designed the Node.js backend, integrated the Claude AI API, and built the Next.js web application.
Testing, optimization & AWS deployment: performed stress testing, prompt verification, and security auditing before live deployment on AWS.
Q1. What is the main takeaway from the AI-Powered Recruitment Platform case study?
Ans. The case study details how Kkeydos developed a custom recruitment portal by using Node.js, Next.js, MongoDB, AWS, and Claude AI to automate the entire recruitment process of resume parsing, candidate scoring and job matching for a US enterprise.
Q2. What kind of AI stack was leveraged for resume parsing and matching?
Ans. We integrated Claude AI APIs along with custom backend algorithms in Node.js to parse resume, extract skills, and calculate candidates compatibility score in real-time against the job requirements.
Q3. How does Claude AI make recruiters' job easier?
Ans. By leveraging Claude AI, unstructured resume data can be read and relevant candidate skills and expertise can be extracted in real-time and a suitability score can be generated against the job requirements, enabling recruiters to focus on the top-scored candidates.
Q4. Can candidates find out about their job fit score on the portal?
Ans. Yes. Candidates gain access to their interactive job-fit scores and profile suggestions in the candidate portal helping them discover the degree to which their profile fits with a particular job before applying.
Q5. Is the candidate information on the portal safe?
Ans. Absolutely. The portal has role-based access control(RBAC), bank-grade API encryption, and is hosted on the secure AWS cloud to ensure candidate personal and professional details remain secure.
Q6. Does the solution allow bulk processing of candidate resumes?
Ans. Yes. The AWS cloud Infrastructure and the backend API framework are designed to process and parse several resume uploads at a time without compromising on performance.
Q7. Does Kkeydos offer to build custom AI portals and HRTech solutions for others as well?
Ans. Yes. Kkeydos is capable of building custom AI-powered web applications, HRTech systems, enterprise SAAS portals and cloud solutions for businesses all over the world.
Q8. What is the average time to develop such an AI platform?
Ans. The typical time to develop a custom enterprise AI portal spans between 6 to 10 weeks depending on system complexity, features in scope and AI implementation.
Q9. Who will hold the intellectual property and source code when the project gets delivered?
Ans. The client is the owner of 100% full ownership of all custom source code, AI prompts, database architecture, cloud setup files and design assets upon launch.
Q10. How can I start my organization's journey to develop custom AI or web applications?
Ans. You can reach out to our team through our contact us page on to discuss your project and get an in-depth strategy proposal.
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