New
User-in-the-loop data engine
The infrastructure layer for relationship AI
From real stories to outcome-driven AI training data
How Hypoll generates data
How Hypoll generates data
How Hypoll generates data
User-in-the-loop judgment engine
Powered by a live consumer system
Is this worth it?
Do I confront this?
Is this normal?
Am I overreacting?
Should I care?
Is this my fault?
Is this a red flag?
What would you do?
Where real dilemmas become data
Powered by a live consumer system
Is this worth it?
Do I confront this?
Is this normal?
Am I overreacting?
Should I care?
Is this my fault?
Is this a red flag?
What would you do?
Where real dilemmas become data
Powered by a
live consumer system
Real outcomes. Better models.
Real outcomes.
Better models.
48-65%
lower cost vs. external pipelines
lower cost vs.
external pipelines
lower cost vs. external pipelines
2–3x
More outcome data
More outcome data
More outcome data
Infinite
Scales with user activity
Scales with user activity
Real outcomes. Better models.
Based on early pilot data
Hypoll use cases
Hypoll use cases
Evaluation
Evaluation
Test model judgment
Test model judgment
Test whether your AI gives realistic, socially aware advice.
Post-training
Post-training
Improve model behavior
Improve model behavior
Train on real dilemmas with outcome-labeled feedback
Audit
Audit
Identify failure modes
Identify failure modes
Find where your model is too agreeable or lacks context.
Integration
Integration
Integrate judgment signals
Integrate judgment signals
Access data via API or custom datasets.
Hypoll use cases
