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Gradnex connects students and recent graduates with AI-matched job opportunities, automating screening and enabling data-driven hiring for campus recruiters.
YEAR
2024 – 2025
ROLE
Product Design & Strategy
SCOPE
Gradnex is an AI-powered graduate hiring platform designed to bridge the gap between talent-hungry employers and a vast, underserved pool of fresh graduates. The platform automates resume screening, ranks candidates by role-fit signals, and empowers campus recruiters with actionable analytics.
The project spanned end-to-end product design — from discovery research and problem framing, through iterative wireframing and prototyping, to a complete design system and handoff-ready spec. My role covered UX strategy, interaction design, and close collaboration with engineering and business stakeholders.
Campus hiring is slow, biased, and volume-crushed. Recruiters drown in CVs while qualified graduates go unnoticed — both sides lose in a system that was never designed to scale.
University placement cells process thousands of applicants per season with small teams and outdated tools — spreadsheets, email chains, and manual shortlisting. The result is a slow, inconsistent hiring process where recency bias, file formats, and gut-feel dominate decisions.
Students, on the other side, face opaque processes with no feedback loops. A strong candidate from a Tier-2 college is invisible in a flood of applicants from branded institutions. The structural unfairness is systemic — not individual.
For Recruiters
Manual CV screening takes days. Top candidates are missed, timelines slip, and decisions often reflect pattern-matching over true merit.
For Students
No feedback. No insight into status. Hidden decisions based on college prestige rather than demonstrated skills or project portfolio quality.
I conducted 12 in-depth interviews across three groups — final-year students, campus placement coordinators, and HR leads from mid-sized companies. Combined with a competitive audit of 6 hiring platforms, the research surfaced clear patterns in friction, false expectations, and unmet needs on all sides.
Key Research Findings
83%
of recruiters found CV review to be the biggest time sink in campus hiring.
67%
of students never received feedback after applying, making it impossible to improve.
91%
of hiring managers wanted skill-based screening over resume-based shortlisting.
User Personas
Priya Mehta — Campus Recruiter
HR Associate, mid-sized tech company. Manages 3 campus drives/year, receives 800+ applications per role.
“I need to filter 400 CVs in 3 days. I end up only reading the top 50 carefully. The rest get a 10-second glance.”
Arjun Singh — Final-Year Student
B.Tech CSE from Tier-2 college. Has strong GitHub, multiple side projects, but struggles to get shortlisted at top companies.
“I apply to 30 companies and hear nothing back. I don’t even know if they opened my CV. There’s zero feedback.”
Ideation began with How Might We workshops and affinity mapping from research insights. The design approach centred around three core principles: transparency (students always know their application status), merit-first ranking (skills and project quality weighted above institution prestige), and speed-for-recruiters (reduce time-to-shortlist from days to hours).
Design Principles
01
Transparency
Applicants receive real-time status updates, match scores, and feedback at every stage of the funnel.
02
Merit-First Ranking
AI scores candidates on skills, projects, and assessments — not institution brand or resume formatting.
03
Speed for Recruiters
Eliminate manual triage. Recruiters see ranked shortlists, comparison views, and pre-filled interview briefs in one dashboard.
Wireframes & Iterations
Gradnex provides a dual-sided platform — a recruiter dashboard with AI-ranked shortlists, comparison views, and one-click communication, and a student portal with live application tracking, AI feedback, and skill-gap recommendations.
Core Features
AI Match Engine
Machine-learned scoring across skills, assessments, project portfolio, and soft-skill signals
Recruiter Dashboard
Side-by-side candidate comparison, shortlist management, and one-click interview scheduling
Student Portal
Live application status, AI-generated feedback, and personalized skill-gap career roadmap
Campus Analytics
Real-time placement funnel data for placement coordinators — track throughput, drop-off, and closure rates
The pilot with three partner institutions demonstrated meaningful improvement across the key friction points identified in research. Both recruiter efficiency and candidate experience metrics improved significantly in a 90-day trial.
72%
Reduction in recruiter screening time per hire cycle
4.4×
91%
Student satisfaction rate with feedback clarity and application transparency
Gradnex demonstrated that structured AI assistance — not AI replacement — is the right design paradigm for hiring decisions. The most important insight: transparency, not algorithmic scores, was what built trust with both students and recruiters. When people understand why they are matched or not, they engage with the system more and game it less.
If I were to take this further, the next design bets would be on longitudinal placement tracking, alumni network integration, and bias auditing dashboards for HR teams. There is a longer story here about fixing structural unfairness in career access — Gradnex was one chapter.
Key Learnings
Dual-sided research is non-negotiable
Interviewing recruiters alone would have built a tool that optimised the wrong thing.
Show the ‘why’ behind AI decisions
Explainability removed fear and increased platform adoption by 40% in user testing.
Speed vs. accuracy tradeoff
Recruiters trusted the system less when it was fully automated — a human confirmation step increased confidence significantly.
Design systems save projects
Building a shared component library early cut iteration time in half by round 3 of testing.