Case Study - AI-Powered Graduate Hiring Platform
Case Study - AI-Powered Graduate Hiring Platform
“Not just the news. The debate. The emotion. The ripple. The revolution.”
“Not just the news. The debate. The emotion. The ripple. The revolution.”
Project Timeline
Project Timeline
Project Timeline
2023
2023
2023
Status
Status
Status
Delivered
Delivered
Delivered
Role
Role
Role
Product Strategy, Product Lead, Project Manager
Product Strategy, Product Lead, Project Manager
Product Strategy, Product Lead, Project Manager
01 OVERVIEW
01 OVERVIEW
The Graduate Hiring Platform is an AI-powered recruitment system designed to assess and hire engineering graduates with minimal human intervention. The platform automates the end-to-end hiring process by leveraging machine learning, cognitive assessments, and behavioral analysis.
The goal: Reduce hiring times, remove bias, scale assessments, and enable data-driven hiring decisions — all while offering a seamless experience to both candidates and recruiters.
The Graduate Hiring Platform is an AI-powered recruitment system designed to assess and hire engineering graduates with minimal human intervention. The platform automates the end-to-end hiring process by leveraging machine learning, cognitive assessments, and behavioral analysis.
The goal: Reduce hiring times, remove bias, scale assessments, and enable data-driven hiring decisions — all while offering a seamless experience to both candidates and recruiters.
02. PROBLEM
02. PROBLEM
Hiring fresh graduates faced significant challenges
Hiring fresh graduates faced significant challenges
Hiring fresh graduates faced significant challenges
Overwhelming Manual Shortlisting
Overwhelming Manual Shortlisting
Recruiters spent weeks sifting through 10k+ resumes, increasing turnaround time and missing top candidates
Recruiters spent weeks sifting through 10k+ resumes, increasing turnaround time and missing top candidates
Bias & Subjectivity
Bias & Subjectivity
Manual screening and interviews risked unconscious bias and inconsistency
Manual screening and interviews risked unconscious bias and inconsistency
Slow Processes
Slow Processes
Extended hiring cycles frustrated both candidates and recruiters
Extended hiring cycles frustrated both candidates and recruiters
Fragmented Experience
Fragmented Experience
Separate systems handled registration, testing, and selection, leading to confusion and errors.
Separate systems handled registration, testing, and selection, leading to confusion and errors.
No Audit Trail
No Audit Trail
Past assessment data and evaluator rationale were not trackable across cycles
Past assessment data and evaluator rationale were not trackable across cycles
Scalability Gaps
Scalability Gaps
Campus season hiring surges often overwhelmed existing workflows
Campus season hiring surges often overwhelmed existing workflows
03. RESEARCH & DISCOVERY
03. RESEARCH & DISCOVERY
To build a solution grounded in real-world challenges, we conducted comprehensive primary research across the three core user groups: students, Training & Placement Officers (TPOs), and HR recruiters. Our goal was to uncover friction points, hidden workflows, and unmet needs that typically go unnoticed in traditional hiring processes
To build a solution grounded in real-world challenges, we conducted comprehensive primary research across the three core user groups: students, Training & Placement Officers (TPOs), and HR recruiters. Our goal was to uncover friction points, hidden workflows, and unmet needs that typically go unnoticed in traditional hiring processes
Research Methodology
Research Methodology
25+ TPO Interviews
25+ TPO Interviews
Conducted structured conversations across Tier 1, Tier 2, and Tier 3 colleges to understand institutional bottlenecks, communication practices, and onboarding workflows.
Conducted structured conversations across Tier 1, Tier 2, and Tier 3 colleges to understand institutional bottlenecks, communication practices, and onboarding workflows.
30+ HR Recruiters
30+ HR Recruiters
Held in-depth sessions with HR stakeholders from conglomerate teams managing large-scale fresher hiring drives. Focus was placed on shortlisting strategy, evaluation criteria, and season-based process failures.
Held in-depth sessions with HR stakeholders from conglomerate teams managing large-scale fresher hiring drives. Focus was placed on shortlisting strategy, evaluation criteria, and season-based process failures.
100+ Final-Year Students
100+ Final-Year Students
Mix of one-on-one interviews, digital surveys, and usability walkthroughs across various disciplines to explore candidate behavior, motivation, and experience pain points.
Mix of one-on-one interviews, digital surveys, and usability walkthroughs across various disciplines to explore candidate behavior, motivation, and experience pain points.
Legacy Campus Hiring - Where It Breaks Down
Legacy Campus Hiring - Where It Breaks Down
Effect of the Broken System
Effect of the Broken System
The Result? Lost talent, Low Efficiency, and High Dropout Rates.
The Result? Lost talent, Low Efficiency, and High Dropout Rates.
Key Insights
Key Insights
1. Students Felt Disconnected
“We register, but then don’t hear back for weeks. No clarity if we’re still in the race.”
Pain Point: Poor or delayed communication led to anxiety and high dropout rates
Implication: Needed automated status updates and transparent tracking modules
“We register, but then don’t hear back for weeks. No clarity if we’re still in the race.”
Pain Point: Poor or delayed communication led to anxiety and high dropout rates
Implication: Needed automated status updates and transparent tracking modules
2. TPOs Faced Operational Overload
"We’re the bridge, but we have no tools. Everything is manual – emails, Excel sheets, phone calls."
Pain Point: Lack of real-time dashboards or batch tracking tools caused errors and delays
Implication: Designed centralized dashboards to reduce manual coordination
"We’re the bridge, but we have no tools. Everything is manual – emails, Excel sheets, phone calls."
Pain Point: Lack of real-time dashboards or batch tracking tools caused errors and delays
Implication: Designed centralized dashboards to reduce manual coordination
3. Recruiters Lacked Consistency in Evaluation
“Two evaluators can rate the same student completely differently. We end up second-guessing decisions.”
Pain Point: Subjective bias in technical and behavioral evaluations
Implication: Introduced AI-powered assessment modules with calibrated scoring
“Two evaluators can rate the same student completely differently. We end up second-guessing decisions.”
Pain Point: Subjective bias in technical and behavioral evaluations
Implication: Introduced AI-powered assessment modules with calibrated scoring
4. No Audit Trail for Decisions
“Once a candidate is rejected, we don’t know why. There's no record, no learning”
Pain Point: No visibility into why candidates progressed or failed
Implication: Added a structured evaluator rationale and performance audit trail
“Once a candidate is rejected, we don’t know why. There's no record, no learning”
Pain Point: No visibility into why candidates progressed or failed
Implication: Added a structured evaluator rationale and performance audit trail
5. Seasonal Scalability Was a Recurring Pain
“During campus season, everything breaks down. We simply can’t scale across 100+ colleges.”
Pain Point: Spikes in application volumes led to errors, lags, and burnout
Implication: Built asynchronous flows, automated communications, and batch-wise orchestration
“During campus season, everything breaks down. We simply can’t scale across 100+ colleges.”
Pain Point: Spikes in application volumes led to errors, lags, and burnout
Implication: Built asynchronous flows, automated communications, and batch-wise orchestration
How Research Shaped the Solution
How Research Shaped the Solution
Created three distinct user flows: Admins (HR), TPOs (Institutes), and Candidates
Prioritized mobile-first, communication-rich design for students
Introduced composite scoring with transparency for HR
Enabled institution-level segmentation and workflows for TPOs
04. DESIGN STRATEGY
04. DESIGN STRATEGY
Approach: Scalable, Transparent, Human-Centric Design
Approach: Scalable, Transparent, Human-Centric Design
Approach: Scalable, Transparent, Human-Centric Design
The core design strategy was built on a three-fold foundation — enabling automation without sacrificing clarity, supporting institutional diversity, and creating trust across every stakeholder interaction.
The core design strategy was built on a three-fold foundation — enabling automation without sacrificing clarity, supporting institutional diversity, and creating trust across every stakeholder interaction.
Key Strategic Pillars
Human-Centric Automation
“Make the experience feel guided, not robotic”
Designed intuitive workflows that minimize friction for students and administrators while allowing AI to handle complexity behind the scenes — such as evaluation, shortlisting, and interview scheduling.
“Make the experience feel guided, not robotic”
Designed intuitive workflows that minimize friction for students and administrators while allowing AI to handle complexity behind the scenes — such as evaluation, shortlisting, and interview scheduling.
Modular & Scalable Platform Architecture
“Every college is different — and so are their processes”
Built a configurable admin backend that allows HRs and TPOs to define eligibility rules, batch timelines, and assessment modules per institute or drive.
“Every college is different — and so are their processes”
Built a configurable admin backend that allows HRs and TPOs to define eligibility rules, batch timelines, and assessment modules per institute or drive.
Trust Through Transparency
“We need to see where each candidate stands — and why"
Embedded live status trackers, audit logs, and explainable AI scoring into the UX to ensure all actions are trackable, reportable, and auditable across hiring cycles.
“We need to see where each candidate stands — and why"
Embedded live status trackers, audit logs, and explainable AI scoring into the UX to ensure all actions are trackable, reportable, and auditable across hiring cycles.
Design Principles That Shaped the UX
Principle
Principle
Why It Matters |
|---|
Why It Matters |
|---|
Design Implication |
|---|
Design Implication |
|---|
Rapid Onboarding |
Rapid Onboarding |
Students face tight schedules and fatigue
Students face tight schedules and fatigue
One-click form autofill, campus code-based smart login, OTP-based validation
One-click form autofill, campus code-based smart login, OTP-based validation
Web - First Experience
Web - First Experience
Candidates need secure proctoring |
Candidates need secure proctoring |
Optimized for desktop browsers with proctor-layer, webcam integration, and timer UX
Optimized for desktop browsers with proctor-layer, webcam integration, and timer UX
|
|
TPOs & HRs need clarity, not clutter |
TPOs & HRs need clarity, not clutter |
Real-time dashboards for candidate movement, completion rates, shortlisting stages
Real-time dashboards for candidate movement, completion rates, shortlisting stages
|
|
Public & private colleges operate differently
Public & private colleges operate differently
Adaptable settings per campus: role-based access, custom notifications, localized rules
Adaptable settings per campus: role-based access, custom notifications, localized rules
|
|
Testing at scale can’t afford system breaks |
Testing at scale can’t afford system breaks |
Auto-save, retry workflows, background verification retries, bulk resync actions
Auto-save, retry workflows, background verification retries, bulk resync actions
UX Considerations by Stakeholders
HR
HR
Custom filters, ranking dashboards, and evaluations
Custom filters, ranking dashboards, and evaluations
Candidate
Candidate
Clarity on next steps, real-time test results, zero ambiguity
Clarity on next steps, real-time test results, zero ambiguity
TPO
TPO
Batch-wise student tracking, bulk communication tools
Batch-wise student tracking, bulk communication tools
05. CONCEPT & MINIMUM VIABLE PRODUCT
To validate the complete end-to-end hiring lifecycle in a controlled environment, we defined a streamlined MVP that would allow HR teams, Training & Placement Officers (TPOs), and students to interact across all major touchpoints — from initiation to onboarding.
The goal: Deliver a working, feedback-ready platform within 24 days that could simulate real hiring outcomes across multiple campuses.
Feature
Description
HR Admin Dashboard |
Launch and configure hiring drives, define eligibility rules, and monitor progress across campuses
|
Enables college TPOs to receive drive details and forward registration links to students
|
Custom form per campus with smart validation, OTP login, and registration success tracking
|
Proctored, time-bound web assessments with secure browser layer and multi-format question types
|
Webcam-based asynchronous interviews scored through AI behavioral analysis and custom rubrics |
|
Automatically generates a final scorecard combining all assessments with weighted logic
|
Auto-save, retry workflows, background verification retries, bulk resync actions
05. CONCEPT & MINIMUM VIABLE PRODUCT
To validate the complete end-to-end hiring lifecycle in a controlled environment, we defined a streamlined MVP that would allow HR teams, Training & Placement Officers (TPOs), and students to interact across all major touchpoints — from initiation to onboarding.
The goal: Deliver a working, feedback-ready platform within 24 days that could simulate real hiring outcomes across multiple campuses.
Feature
Description
HR Admin Dashboard |
Launch and configure hiring drives, define eligibility rules, and monitor progress across campuses
|
Enables college TPOs to receive drive details and forward registration links to students
|
Custom form per campus with smart validation, OTP login, and registration success tracking
|
Proctored, time-bound web assessments with secure browser layer and multi-format question types
|
Webcam-based asynchronous interviews scored through AI behavioral analysis and custom rubrics |
|
Automatically generates a final scorecard combining all assessments with weighted logic
|
Auto-save, retry workflows, background verification retries, bulk resync actions
05. CONCEPT & MINIMUM VIABLE PRODUCT
To validate the complete end-to-end hiring lifecycle in a controlled environment, we defined a streamlined MVP that would allow HR teams, Training & Placement Officers (TPOs), and students to interact across all major touchpoints — from initiation to onboarding.
The goal: Deliver a working, feedback-ready platform within 24 days that could simulate real hiring outcomes across multiple campuses.
Feature
Description
HR Admin Dashboard |
Launch and configure hiring drives, define eligibility rules, and monitor progress across campuses
|
Enables college TPOs to receive drive details and forward registration links to students
|
Custom form per campus with smart validation, OTP login, and registration success tracking
|
Proctored, time-bound web assessments with secure browser layer and multi-format question types
|
Webcam-based asynchronous interviews scored through AI behavioral analysis and custom rubrics |
|
Automatically generates a final scorecard combining all assessments with weighted logic
|
Auto-save, retry workflows, background verification retries, bulk resync actions
06. USER TESTING & LEARNING
06. USER TESTING & LEARNING
Participants
Participants
120+ students |
120+ students |
from Tier 2 and Tier 3 colleges
from Tier 2 and Tier 3 colleges
Placement Officers |
Placement Officers |
from participating institutions
from participating institutions
Recruiters and HR |
Recruiters and HR |
teams from multiple business units
teams from multiple business units
Observation
Observation
Insight & Impact
Insight & Impact
Adaptive Assessments Improved Completion |
Adaptive Assessments Improved Completion |
Context-aware, timed assessments resulted in higher student completion rates and better engagement.
Context-aware, timed assessments resulted in higher student completion rates and better engagement.
Progress Bars Reduced Dropouts |
Progress Bars Reduced Dropouts |
Clear visual indicators of test and interview progress boosted student confidence and reduced mid-process exits. |
Clear visual indicators of test and interview progress boosted student confidence and reduced mid-process exits. |
AI Interviews Gained Acceptance Post-Redesign
AI Interviews Gained Acceptance Post-Redesign
Simplified UI, empathetic prompts, and real-time support increased trust in AI-led interview flows.
Simplified UI, empathetic prompts, and real-time support increased trust in AI-led interview flows.
Composite Score Transparency Appreciated |
Composite Score Transparency Appreciated |
Recruiters valued the ability to view and filter candidates by skill clusters and score explainability, enabling more confident shortlisting.
Recruiters valued the ability to view and filter candidates by skill clusters and score explainability, enabling more confident shortlisting.
Network Access Issues Identified |
Network Access Issues Identified |
Some colleges faced challenges accessing the platform due to restrictive firewalls and slow internet; this informed fallback solutions. |
Some colleges faced challenges accessing the platform due to restrictive firewalls and slow internet; this informed fallback solutions. |
07. FINAL PLATFORM FEATURES
07. FINAL PLATFORM FEATURES
08. RESULT & IMPACT
08. RESULT & IMPACT
Key Metric
Key Metric
Key Metric
Metric
Metric
Metric
|
|---|
|
|---|
|
|---|
|
|---|
|
|---|
|
|---|
Time to Hire |
Time to Hire |
6–8 weeks
6–8 weeks
2.5 weeks
2.5 weeks
Recruiter Screening Hours
Recruiter Screening Hours
|
|
~100 hrs
~100 hrs
|
|
~28% |
~28% |
<10%
<10%
|
|
3.2 / 5
3.2 / 5
4.7 / 5 |
4.7 / 5 |
|
|
60% |
60% |
86%
86%
Impact Summary
Impact Summary
Impact Summary
Massive reduction in recruiter workload through AI-led shortlisting and assessments.
Higher candidate engagement and trust due to clear communication and real-time status updates.
Improved institutional coordination with transparent dashboards for TPOs and automated scheduling.
Better hiring outcomes with a significant lift in offer acceptance and reduced dropouts.
Massive reduction in recruiter workload through AI-led shortlisting and assessments.
Higher candidate engagement and trust due to clear communication and real-time status updates.
Improved institutional coordination with transparent dashboards for TPOs and automated scheduling.
Better hiring outcomes with a significant lift in offer acceptance and reduced dropouts.
Lessons Learned
Lessons Learned
Lessons Learned
Systems must adapt to institutional variability — one-size-fits-all fails in higher ed
Trust in AI grows when paired with human transparency and clear feedback
A great candidate experience drives engagement more than flashy tech
Operational visibility for HR is key to adoption
Systems must adapt to institutional variability — one-size-fits-all fails in higher education
Trust in AI grows when paired with human transparency and clear feedback
A great candidate experience drives engagement more than flashy tech
Operational visibility for HR is key to adoption
09. CONCLUSION
09. CONCLUSION
This platform is a glimpse into the future of enterprise hiring — where AI supports scale, but the experience remains deeply human. By simplifying and automating graduate hiring, we helped redefine recruitment for one of India’s largest conglomerates, proving that speed, fairness, and personalization can coexist in a single system.
This platform is a glimpse into the future of enterprise hiring — where AI supports scale, but the experience remains deeply human. By simplifying and automating graduate hiring, we helped redefine recruitment for one of India’s largest conglomerates, proving that speed, fairness, and personalization can coexist in a single system.