Context
What the participant wants and sees.
Human workflow data for AI agents
Train agents on human work.
Learn howWe study how people complete digital tasks—then turn those journeys into data AI agents can learn from.
Market research is the method. Agent-ready data is the product.
The first hour
The first hour holds the richest signals.
We connect intent, action, friction and outcome.
- Sign up
- Set up
- First value
What we capture
A click is not a journey.
We capture what happened around it.
Journey
Actions, friction and recovery.
Outcome
What happened, with human-reviewed labels.
How it works
From study to dataset.
Consented sessions become de-identified, labeled trajectories.
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01
Scope
Authorized task and use.
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02
Capture
Consenting participants.
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03
Structure
De-identify and label.
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04
Validate
Review quality and limits.
Planned products
Data built around the task.
Custom task data
New research for one workflow.
Workflow datasets
Labeled traces with provenance.
Evaluation sets
Documented edge cases for testing.
Responsible data
Trust is part of the dataset.
Participants choose whether to take part. Studies are authorized, sensitive fields are excluded, and direct identifiers are removed or transformed.
- Clear consent
- Defined use
- Documented limits
Reviews
Sample review
“The steps were clear, and I always knew what came next.”
Sample review
“It was quick to get started and easy to understand.”
Sample review
“I appreciated knowing what information was being collected.”
Sample review
“The instructions felt straightforward from beginning to end.”
Sample review
“I could move through the study without guessing.”
Sample review
“The process felt organized, simple, and respectful.”
Contact
What should your agent learn next?
Tell us about the workflow, research question, or evaluation your team is working on.
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Ottawa, Ontario K1N 8S7
Canada
Ottawa, Ontario K1N 8S7
Canada