Designing the QLU Ecosystem
How we transformed a grueling, manual executive search process into an AI-powered ecosystem, cutting research time by 92% and operational costs by 86%.
ROLE
Product Designer
Led Design across
3 connected products
OUTCOME
92% faster shortlists
86% lower cost
65% productivity lift
DURATION
14 months
Prologue: The Context
Executive search is a high-stakes game. When a company needs a new CEO, CTO, or CFO, they aren't just filling a seat; they are looking for a needle in a global haystack.
Before QLU, I learned that finding that needle was an agonizingly slow, manual process. Recruiters would gather requirements, scour internal databases, manually hunt across external platforms, build an initial list, and pray the Hiring Manager approved the direction. Then came the cold outreach, the fragmented tracking, and the waiting.
The result? 6 to 8 months just to build the initial candidate pipeline. Recruiters were acting as human data scrapers, burning out before the actual interviews even began. We didn't just need a new tool; we needed to automate the entire ecosystem.
Chapter 1: Empathy at Scale (Research)
To fix this, our team put in the long hours. We didn't just build in a vacuum; we partnered with officials from Spencer Stuart to not only identify the problem but validate it.
We conducted hundreds of meetings with cross-functional teams and watched countless user sessions to deeply empathize with the executive recruiter's psychology. We realized that while they needed automation, they were terrified of losing the "human touch" that defined their profession.
As the Lead Product Designer, I owned the end-to-end design of this ecosystem.
I designed 60% of our core module, QLU Research, and took the absolute lead in designing QLU Outreach and QLU Dialer. My design mandate was clear: build powerful AI tools that felt intuitive, whether the user was a tech-savvy early adopter or a traditional recruiter.
Chapter 2: QLU Research (From 8 months to 5 mins)
The first hurdle was data gathering. We built a massive local database fed by LinkedIn, Glassdoor, Crunchbase, and more. But data is useless if it's hard to access.
Knowing our users had varying levels of tech-savviness, I designed a dual-interface approach for QLU Research. For recruiters comfortable with AI, a conversational chat interface allowed them to type complex requirements naturally. For traditionalists, I designed an advanced, intuitive filter system.
Within 5 minutes, a recruiter could generate a highly targeted list. As they refined their search, the AI learned and improved the results. Once the perfect candidates were found, they could be saved into "Assignments" (folders) and instantly shared with the Hiring Manager via a secure link, PDF, or Excel, eliminating the dreaded feedback loop delay.
Chapter 3: QLU Outreach (Crafting the Perfect Pitch)
Finding the candidate is only half the battle; getting them to reply is the other. With QLU Outreach, I designed a seamless bridge from research to engagement.
Recruiters could import their lists directly from QLU Research or upload their own Excel sheets (First Name, Last Name, Company, Position, LinkedIn, Email, Contact). The magic happened in the drafting phase. I designed an AI assistant that helped recruiters craft highly personalized outreach messages based on the candidate's background.
Recruiters could select their channel, hit send, and watch as the system worked in the background. When a response came in, the platform automatically updated the candidate's status in their Assignment folder to "Interested" or "Not Interested."
Chapter 4: QLU Dialer (The AI Co-pilot for taking interviews)
When a C-level executive says "I'm interested," the recruiter has one shot to make an impression. This is where I led the design of the QLU Dialer.
For candidates marked "Interested," recruiters could schedule a meet directly through the Dialer. But I wanted to give recruiters an unfair advantage. I designed an AI assistant that generates a pre-call agenda based on the candidate's profile.
During the call, the AI acts as a co-pilot, providing real-time suggestions and talking points. Once the call ends, it automatically generates a comprehensive report, ensuring no detail is lost and the recruiter can immediately move to the next step of the company's placement procedure.
Chapter 5: The Impact
92%
Time reduced to
source initial profiles.
86%
Cost reduction to operate assignments
(Dropping from $180,000 to $25,000).
65%
Increase in
Recruiter's productivity.
Chapter 6: Learnings
Building QLU taught me that the best AI doesn't replace the human; it elevates them. Executive recruiters rely on intuition, relationship-building, and emotional intelligence. By designing an ecosystem that handled the data scraping, the outreach tracking, and the call note-taking, we gave recruiters their time back to do what they do best.
As a Product Designer, my biggest takeaway was the importance of flexible onboarding. By offering both an AI chat interface and traditional filters in QLU Research, we ensured that no user was left behind in the transition to AI. We didn't just build a tool; we built a partner for the modern recruiter.