
from concept to live
Analyzed conversations
end-to-end ownership
STACK
The brief
UX and product teams rely on qualitative insight, but analyzing thousands of real conversations is slow, manual, and inconsistent.
Humyn explores how AI can make qualitative research fast, trustworthy, and usable.
Context and insight
Teams track metrics in real time, but qualitative insight lags by days or weeks.
When interpretation is rushed, nuance is lost and confidence drops.
The Problem
Solution and product
Project Snapshot
Quick status: comments ingested, latest sync, highlight summaries, runs processed.
Add Comments
Batch threads with topic + keywords to guide relevance.
Explore with links
Skimmable summaries, topics, and aspects, each with a link back to the original Reddit comment.
Metrics
Overall sentiment and stacked sentiment by aspect to see what drives reactions.
AI Chat
Natural questions, cited answers, one-click jump to Explore.
Design and constraints
Clarity over decoration.
Low fidelity flows exposed friction early
High fidelity designs were shaped by real engineering limits
Minimal UI built with shadcn/ui
Every screen tied back to a single research question
If it does not answer the core question, it is bloat
If it is slow, static, or inaccurate, trust breaks
Brand, growth and launch
I led growth through product driven storytelling and community feedback loops:
2,000 plus followers across social platforms
500 plus Discord testers
500 plus waitlist signups
Goal
Ship clean. Reduce risk. Enable iteration.
Follow our socials here!
Current state & reflection
Humyn is live in closed beta.
View More






















