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The loudest opinions are easy to find. The representative ones aren't. Ask one question and TruTake turns answers into audience perspectives, stories, media, and creator-ready reports.

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Do you feel safer or less safe in your neighborhood compared to a year ago?

21
Answers
2h 43m
Window
3
Formations
1
Tensions

The crowd is surprised at the outcome.

Crowd Signal - Prediction Pressure - Medium

Magnitude
Audience Topology

Hidden knowledge in the crowd

See the formations, belief patterns, demographic compositions, calibration bars, and synthetic media characters that emerge from one question.

24%
confident aligner5 people

Confident Aligners

No change + Expected No change

Synthetic media character representing Lauren Mitchell

Synthetic media character

Lauren Mitchell

39 · Technology worker · New York

A 39-year-old female-presenting technology worker in New York who believes things will see no change and confidently expects most others feel the same, reinforcing the core consensus.

About 24% of people chose “No change” and expected “No change” to be the most common answer. They matched the dominant view and correctly anticipated that others would feel the same way. This group reinforces the core consensus.

Believed
No change
Expected crowd
No change
Highest calibration
rank 1
Score100
Signal100
Accuracy100
Skews Female · 60%Mostly California and New York · 80%
24%
majority but uncertain5 people

Positive but Unsure

No change + Expected Less safe

Synthetic media character representing Ethan Ramirez

Synthetic media character

Ethan Ramirez

29 · Technology worker · New York

A 29-year-old male-presenting technology worker in New York who personally expects no change but assumes most others feel less safe, reflecting a misread of the broader consensus.

About 24% of people chose “No change” and expected “Less safe” to be the most common answer. They shared the dominant view, but underestimated how widely it would be shared. This group is key to correcting the misread consensus.

Believed
No change
Expected crowd
Less safe
Lower calibration
rank 3
Score58
Signal100
Accuracy29
Mostly 25_34 · 80%Skews Male · 60%Mostly New York and New Jersey · 80%
24%
confident dissenter5 people

Confident Dissenters

Less safe + Expected Less safe

Synthetic media character representing Marcus Lee

Synthetic media character

Marcus Lee

29 · New York

A 29-year-old male-presenting New Yorker who feels things are less safe and expects most others to feel less safe as well, confidently dissenting from the overall majority view.

About 24% of people chose “Less safe” and expected “Less safe” to be the most common answer. They held a less common view and expected it to be more common than it was. This group may feel more common than it is in the broader audience.

Believed
Less safe
Expected crowd
Less safe
Lowest calibration
rank 8
Score1
Signal1
Accuracy29
Mostly 25_34 · 60%Skews Male · 60%Mostly New York · 100%
Synthetic aggregate persona representing Lauren Mitchell
Lauren Mitchell
Technology worker · New York
5 people
Synthetic aggregate persona representing Ethan Ramirez
Ethan Ramirez
Technology worker · New York
5 people
Audience formations become story assets

From audience tension to story assets

TruTake identifies synthetic personas inside your audience, then turns their tension into media you can publish, study, or reuse.

Creators retain full rights to distribute and monetize their story assets. Creator Toolkit terms

Mini podcast
Photo story
Article draft

Two aggregate audience personas. One generated story package.

Generative media
Alternative Media

Stories built from real people's beliefs, not one person's voice

TruTake generates mini podcasts, comics, and clips anchored in the truth from your audience. See your community come to life in storyform with every question.

AI-generated documentary photo strip for this story

AI MEDIAGenerated from the crowd responses

EPISTEMIC SENSORS

Detect cognitive patterns in your audience in real time

TruTake continuously scans for hidden structures, disagreements, calibration gaps, and emerging audience belief formations.

Blind spotsOverconfidenceAudience splitsGender skewsAge divergenceLocation anomalyCareer clustersAccuracy gapsHidden consensusEmerging formationsMemetic hazardsNew sensors added continuously
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