Case Study
Rethinking Interview Scheduling with LLM
Secondary Research
User Journey Mapping
Case Study
Rethinking Interview Scheduling with LLM
Secondary Research
User Journey Mapping
Case Study
Rethinking Interview Scheduling with LLM
Secondary Research
User Journey Mapping
Project Overview
Project Overview
The emergence of LLMs has pushed many industries to rethink how to reduce manual, repetitive work without compromising human control. An AI assistant was designed as an assistive AI experience powered by LLM, focused on helping recruiters track work, prioritize actions, and reduce operational effort. Rather than automating decisions, the system supports users with contextual assistance, keeping accountability and final decision-making firmly in human hands.
The emergence of LLMs has pushed many industries to rethink how to reduce manual, repetitive work without compromising human control. An AI assistant was designed as an assistive AI experience powered by LLM, focused on helping recruiters track work, prioritize actions, and reduce operational effort. Rather than automating decisions, the system supports users with contextual assistance, keeping accountability and final decision-making firmly in human hands.
The emergence of LLMs has pushed many industries to rethink how to reduce manual, repetitive work without compromising human control. An AI assistant was designed as an assistive AI experience powered by LLM, focused on helping recruiters track work, prioritize actions, and reduce operational effort. Rather than automating decisions, the system supports users with contextual assistance, keeping accountability and final decision-making firmly in human hands.
Timeline
Timeline
Timeline
Apr - May 2023
Apr - May 2023
Apr - May 2023
Team
Team
Team
1 Senior UX Designer
1 UX Designer
1 Product Manager
1 Senior UX Designer
1 UX Designer
1 Product Manager
1 Senior UX Designer
1 UX Designer
1 Product Manager
My Role
My Role
My Role
We initially conducted secondary research: I studied other HR companies' AI proposals, and my colleague studied the ethical side of AI.
Initial wireframes of how AI will interact
User journey map for easy understanding.
Later, we picked up different use cases and worked through them in detail.
We initially conducted secondary research: I studied other HR companies' AI proposals, and my colleague studied the ethical side of AI.
Initial wireframes of how AI will interact
User journey map for easy understanding.
Later, we picked up different use cases and worked through them in detail.
We initially conducted secondary research: I studied other HR companies' AI proposals, and my colleague studied the ethical side of AI.
Initial wireframes of how AI will interact
User journey map for easy understanding.
Later, we picked up different use cases and worked through them in detail.
Process
Process
Secondary Research
Secondary Research
GPT-integrated features in other competitive products
GPT-integrated features in other competitive products
GPT-integrated features in other competitive products
Personalised job recommendations for candidates.
Tailored referrals
Intelligent search based on user intent and natural language processing
Intelligent Sourcing
Automated interview scheduling & tasks
Job insights
Data-driven skills insights for employee progress
Personalisation of assistive technology as per use.
Candidate engagement through personalised messages & reminders
Analytics & Insights on talent acquisition
Personalised job recommendations for candidates.
Tailored referrals
Intelligent search based on user intent and natural language processing
Intelligent Sourcing
Automated interview scheduling & tasks
Job insights
Data-driven skills insights for employee progress
Personalisation of assistive technology as per use.
Candidate engagement through personalised messages & reminders
Analytics & Insights on talent acquisition
Personalised job recommendations for candidates.
Tailored referrals
Intelligent search based on user intent and natural language processing
Intelligent Sourcing
Automated interview scheduling & tasks
Job insights
Data-driven skills insights for employee progress
Personalisation of assistive technology as per use.
Candidate engagement through personalised messages & reminders
Analytics & Insights on talent acquisition
Ideation
Ideation
User
User
Recruiter
Recruiter
Recruiter
From sourcing to onboarding
From sourcing to onboarding
From sourcing to onboarding
Interviewer
Managing interviews, creating an interview questionnaire, and providing feedback
Approver
Domain knowledge and correct decisions.
Hiring Manager
From creating requisition to approval
Candidate
Finding suitable jobs
Employee
Upscaling and upgrading
Interviewer
Interviewer
Managing interviews, creating an interview questionnaire, and providing feedback
Managing interviews, creating an interview questionnaire, and providing feedback
Approver
Approver
Domain knowledge and correct decisions
Domain knowledge and correct decisions
Hiring Manager
Hiring Manager
From creating requisition to approval
From creating requisition to approval
Candidate
Candidate
Finding suitable jobs
Finding suitable jobs
Employee
Employee
Upscaling and upgrading
Upscaling and upgrading
Incentive to use
Incentive to use
Recruiters perform monotonous, repetitive tasks, which an AI assistant can alleviate. Each task has multiple subparts that it can handle.
Research assistance will help users get work done easily.
Help in the analysis of skills, fitments, interviews, etc.
Candidate & task tracking.
Recruiters perform monotonous, repetitive tasks, which an AI assistant can alleviate. Each task has multiple subparts that it can handle.
Research assistance will help users get work done easily.
Help in the analysis of skills, fitments, interviews, etc.
Candidate & task tracking.
Recruiters perform monotonous, repetitive tasks, which an AI assistant can alleviate. Each task has multiple subparts that it can handle.
Research assistance will help users get work done easily.
Help in the analysis of skills, fitments, interviews, etc.
Candidate & task tracking.
The AI assistant will only help the user and simplify everyday tasks. The final decisions will always remain with the user.
The AI assistant will only help the user and simplify everyday tasks. The final decisions will always remain with the user.
The AI assistant will only help the user and simplify everyday tasks. The final decisions will always remain with the user.
Focus Area
Focus Area
After mapping the end-to-end user journeys, I narrowed my focus to the scheduling interviews flow, which I explored in depth based on a discussion with our co-founder and its importance to the overall hiring experience.
After mapping the end-to-end user journeys, I narrowed my focus to the scheduling interviews flow, which I explored in depth based on a discussion with our co-founder and its importance to the overall hiring experience.
After mapping the end-to-end user journeys, I narrowed my focus to the scheduling interviews flow, which I explored in depth based on a discussion with our co-founder and its importance to the overall hiring experience.
User Journey Map
User Journey Map
Scheduling Interview
Scheduling Interview
Page Layout
Page Layout
In the initial project phase, I designed a floating chat window that users can freely move on the screen. This feature allows users to initiate conversations at any point within the application, ensuring seamless support access regardless of the current page.
In the initial project phase, I designed a floating chat window that users can freely move on the screen. This feature allows users to initiate conversations at any point within the application, ensuring seamless support access regardless of the current page.
In the initial project phase, I designed a floating chat window that users can freely move on the screen. This feature allows users to initiate conversations at any point within the application, ensuring seamless support access regardless of the current page.
As we went deeper into the focused areas, we realized that a floating chat alone would not fully support users at the moments they needed help most. To create a more effective experience, we paired the floating window with in-field assistance, offering guidance directly within the context of the task.
As we went deeper into the focused areas, we realized that a floating chat alone would not fully support users at the moments they needed help most. To create a more effective experience, we paired the floating window with in-field assistance, offering guidance directly within the context of the task.
As we went deeper into the focused areas, we realized that a floating chat alone would not fully support users at the moments they needed help most. To create a more effective experience, we paired the floating window with in-field assistance, offering guidance directly within the context of the task.
Hi-Fidelity Design
Hi-Fidelity Design
The recruiter enters the candidate’s name. The AI assistant identifies the relevant job and candidate details, then confirms them with the recruiter before scheduling the interview.
The recruiter enters the candidate’s name. The AI assistant identifies the relevant job and candidate details, then confirms them with the recruiter before scheduling the interview.
The recruiter enters the candidate’s name. The AI assistant identifies the relevant job and candidate details, then confirms them with the recruiter before scheduling the interview.
As per the previous interviews scheduled with the interviewer, the AI assistant will suggest preferred time slot to the recruiter.
As per the previous interviews scheduled with the interviewer, the AI assistant will suggest preferred time slot to the recruiter.
As per the previous interviews scheduled with the interviewer, the AI assistant will suggest preferred time slot to the recruiter.
The AI assistant connects with the interviewer over email and WhatsApp to gather preferred time slots, handling the back-and-forth automatically. Once the interview is scheduled, the recruiter is notified.
Before the interview, when the interviewer logs into the portal, the assistant steps in again, offering a quick overview of the candidate along with relevant context and suggested questions to help them walk in prepared.
The AI assistant connects with the interviewer over email and WhatsApp to gather preferred time slots, handling the back-and-forth automatically. Once the interview is scheduled, the recruiter is notified.
The AI assistant connects with the interviewer over email and WhatsApp to gather preferred time slots, handling the back-and-forth automatically. Once the interview is scheduled, the recruiter is notified.
Before the interview, when the interviewer logs into the portal, the assistant steps in again, offering a quick overview of the candidate along with relevant context and suggested questions to help them walk in prepared.
Before the interview, when the interviewer logs into the portal, the assistant steps in again, offering a quick overview of the candidate along with relevant context and suggested questions to help them walk in prepared.