Meet PIA
How we transformed AI from a chatbot into a structured decision-making system for hiring
Background
After leaving Infuy, the technology consultancy he co-founded, Martin Liguori saw an opportunity to build products around the rapid evolution of generative AI. Rather than creating another conversational assistant, the vision was to rethink one of the most expensive and inconsistent business processes: recruitment. Hiring still depends heavily on manual interviews, subjective evaluations, and recruiter availability. Meetpia set out to redesign this process by combining conversational AI with structured assessments capable of scaling interviews while maintaining transparency and consistency.
Challenge
Designing an AI interviewer introduced challenges that extended far beyond interface design. Candidates needed conversations that felt natural, while recruiters required results they could confidently trust when making hiring decisions. The core challenge was balancing conversational flexibility with standardized evaluation. Every interaction needed to adapt to the candidate's responses while producing consistent outputs across interviews. At the same time, the platform had to communicate how conclusions were reached, avoiding the "black box" effect commonly associated with AI-driven products.
Process
Designing Meetpia required treating conversation itself as the primary interface. Rather than focusing exclusively on screens, the project revolved around structuring decision flows, defining evaluation models, and translating complex AI reasoning into experiences that felt transparent for both candidates and recruiters.
PHASE 1
Understanding Recruitment Workflows
PHASE 2
Translating Workflows into a Design System
PHASE 3
Evaluating AI Capabilities
PHASE 4
Turning Data into Recruiter Insights
PHASE 5
Refining Through Continuous Validation
Measured impact and results
