Designed for a client. Built for a platform: Optimized interview workflow and AI-powered kit
B2B | B2C
Recruitment Automation
About Vasitum
Vasitum is an end-to-end AI recruitment automation platform [part ATS, part intelligent hiring engine], trusted by companies ranging from TCS and Snapdeal to fast-growing startups across India.
I worked at Vasitum as the sole product designer. My first PRD was an ambitious one: design an entirely new interview flow for the recruiter-facing dashboard, covering both multi-round scheduling and a purpose-built interview kit for interviewers.
What we realised early on was that this wasn't just a client deliverable, but a gap in our own platform that every recruiter on Vasitum would benefit from. The goal shifted: build for one, design for all.
Team:
1 Designer · 3 Frontend Devs · 2 Backend Devs · 2 AI Scientist · 1 Product Manager
My Contribution:
Solo Product Designer
Timeline:
Jan 2024 - Mar 2024
Challenge
Scheduling interviews is a deceptively complex task
Recruiters juggle multiple candidates, multiple rounds, and multiple interviewers, each with their own availability, while navigating last-minute changes and tracking everything manually. The complexity compounds as the number of applicants grows.
On the interviewer side, the problem is different but equally painful: going into sessions cold, with no context from prior rounds, no standardised way to evaluate, and no structured way to record feedback without bias.
6 weeks, hard deadline
A long-term client needed features live before their membership renewal. It had to be complete, polished, and production-ready by a fixed date.
Solo designer, full scope
Responsible for everything from research through to final handoff, no second pair of eyes, and engineers already mid-sprint on other work.
Build once, serve everyone
The client's request had to be abstracted into a generalised system- something other users on the platform could use from day one of rollout.
Research & Discovery
Understanding the landscape
With a tight timeline, running a lengthy research phase wasn't an option. Instead I leveraged Vasitum's own large HR department as a live research panel; people using recruitment tools every single day. Their frustrations were immediate, unfiltered, and directly relevant to what we were building.
I ran focused sessions with internal recruiters, then cross-referenced their input with perspectives from our Growth Head to understand the business and platform retention angle and Senior Developers who regularly interview candidates, to understand what it actually feels like to be on the other side of the table.
Some valuable Insights:
Multi-round chaos: No single view to track where each candidate stood across rounds. Everything lived in inboxes and spreadsheets.
Confused interviewers: No context shared before sessions, no previous scores, candidate background, or what was already assessed.
No standardised scoring: Feedback was informal, subjective, and incomparable making final hiring decisions inconsistent and hard to justify.
Manual question prep: Interviewers spent 30–45 minutes per session preparing questions, time AI could reclaim entirely.
Candidate drop-off: Slow, disjointed scheduling caused candidates to disengage before even reaching the first interview round.
"I'm scheduling the same candidate four times, one email per round, different interviewer each time, all manual."
— Recruiter, Vasitum Internal HR Team
"I walk into most interviews without knowing what was assessed in round one. Half the time I'm repeating the same questions."
— Senior Developer, interviewed as hiring manager
"Comparing candidates after final rounds is nearly impossible. Everyone scores differently because there's no shared rubric."
— Growth Head, on post-interview decision making
Solution Overview
We designed two primary flows that work together
The recruiter's flow handles orchestration: creating round templates, scheduling candidates, and tracking scores. The Interview Kit handles the experience on the interviewer's side of the table.
Together they close the loop between scheduling and execution; giving recruiters clarity and giving interviewers the context they need to run structured, informed interview sessions.
Recruiter's Flow
Create multi-round interview templates per job posting
Create multiple rounds for the role with an option to use premade round templates
Track per-candidate interview status across all rounds
View consolidated results and scorecards post-interview
Interview Kit (For Interviewers)
Shareable link to the kit, no Vasitum account required
Candidate profile summary + prior round context along with interview instructions.
AI-generated question bank to assist the interviewers
Structured scorecard with relevant attributes
Design
Recruiter's Flow: Creating interview rounds for a job
The flow starts with a CTA to create a new interview schedule. The recruiter selects the number of rounds for a specific job posting. Empty round templates are generated, each with key fields to fill: round type, interviewer, duration, and assessment focus.
Once saved, these templates are reusable across all candidates for the same role eliminating the need to re-enter round structures every time an applicant progresses.
Design rationale:
Most platforms treat scheduling as a one-off event. We inverted this, making the template the primary object, and each individual scheduling action a derivation from it. This mirrors how recruiters actually think: they define the interview process per role, not per candidate.
Template-first approach: define the process once, reuse it across all candidates
Round types mapped to assessment category (Technical, HR, Cultural Fit, etc.)
Pre-filled fields on subsequent scheduling reduce input effort significantly
Recruiter's Flow: Scheduling an interview for a candidate
From the candidate's application window, the recruiter selects the relevant round based on the applicant's current stage. The pre-filled template loads automatically (interviewer, round type, and structure already populated) requiring only a date and time to confirm.
This reduces scheduling from a multi-step manual process to a near-instant action, directly from within the candidate's profile.
Design rationale:
Recruiters were losing the most time to repeat data entry, re-entering identical round details for every candidate. Anchoring the schedule to the job's pre-built template turned a 10-minute manual task into a 45-second action.
Only rounds relevant to the candidate's current stage are shown
Pre-filled form removes repetitive data entry on every scheduling action
Automated candidate notification triggered automatically on confirmation
Interview Kit: Everything the interviewer needs, before they walk in
The Interview Kit is sent to the interviewer before the session begins as a shareable link that works whether or not they're a Vasitum user. It surfaces the candidate's key profile details, instructions for the interview, and an AI-generated question bank tailored to the round type and role.
The kit also contains a live scorecard so feedback is captured in real time during the interview, not reconstructed from memory afterwards.
Why AI question generation matters here:
Interviewers were spending significant time on question prep. The AI eliminates this entirely by generating a contextual bank on demand, with the interviewer free to use, adapt, or discard as they see fit.
Questions are generated based on job role, round type (Technical, Behavioural, Cultural Fit), so each session genuinely builds forward rather than looping back.
Candidate summary auto-populated from their Vasitum profile
Shareable link: no login required for third-party or external interviewers
Score Card: Structured Feedback
One of the clearest pain points from research was the inconsistency of post-interview feedback. Every interviewer had their own informal rating system or none at all making it nearly impossible to compare candidates across rounds.
The scorecard standardises this entirely: predefined atributes, a consistent rating scale, and a freeform notes field. The recruiter then sees a consolidated view across all rounds enabling data-informed decisions rather than gut-feel ones.
Design rationale:
Scoring should happen during the interview, not after. The scorecard is embedded directly in the Interview Kit so the interviewer rates as the conversation unfolds, while observations are still fresh.
Consistent rating scale across all interviewers and sessions
Consolidated recruiter view across all completed rounds
Impact & Outcomes
"The ask of our client ended up becoming something the entire platform benefits from. The scheduling flow removed hours of manual coordination from our week, and the interview kit meant our external interviewers are actually prepared for the first time."
— Growth Head, on post-interview decision making
∞
New features was adopted platform wide increasing improving recruiter speed and satisfaction.
10m→45s
Reduction in time it takes for recruiter to schedule multiple rounds of interviews for a similar roles
Reflection
What I'd take forward
This project set the tone for how I approach design under resource constraints. When time and bandwidth are limited, the instinct is to cut scope. What I learned instead is to cut friction: in process, in communication, in the work itself.
Being the only designer also demanded a kind of rigor I hadn't practiced before. Every decision had to stand on its own; grounded in the research, aligned with technical reality, and designed to scale beyond the immediate ask.
Lesson 01
Use what's already in the room
Our internal HR team was an underutilized research asset. Good research doesn't require long timelines, it requires the right questions aimed at the right people.
Lesson 02
Client asks are platform signals
The best product features often start as bespoke requests. The real design work is finding the universal pattern inside the specific problem and building the version that serves everyone.
Lesson 03
Ship components, not screens
Releasing components to engineers as they were defined and not after the full design was finished, shortened the build cycle without any quality tradeoff.
