01
Human-Centric AI
Use automation to support better judgment, not replace human accountability.
About Talent Decoder
Building objective talent signals for better career decisions.
Talent Decoder helps companies move from fragmented hiring evidence to structured, explainable, and privacy-aware talent intelligence.
Founder story
Career science, enterprise AI, and a sharper hiring operating system.
Talent Decoder was built to close the gap between human intuition and repeatable evidence. The goal is a recruiting workflow where teams can inspect why a candidate fits, what risk remains, and which next step is justified.
Herman Fong
Founder and CEO
Stanford MSc / ex-Gridsum Data Intelligence
Core Values
02
Objective Talent Signals
Bring clearer evidence into decisions that are too often scattered or subjective.
03
Data-Driven Decisions
Connect hiring outcomes, assessment signals, and team learning loops.
04
Responsible Automation
Make confidence, source boundaries, and review requirements visible.
05
Continuous Growth
Treat candidate profiles and assessment output as long-term development input.
06
Trust and Privacy
Design every workflow around sensitive employee and candidate information.
Join our team
Build the talent command center.
We are looking for people who care about high-trust interfaces, applied AI, and practical tools for better career decisions.
Product Engineer
Build the hiring command center and assessment UX.
AI Workflow Engineer
Design reliable agent flows for HR policy work.
Product Designer
Shape dense, high-trust enterprise interfaces.
Talent Science Lead
Turn assessment methodology into practical product.