Databrain AI

Predict whether a creative will capture attention before you spend on media.

Creative pretesting with models trained on biometric data, eye tracking and applied neuroscience. A clear read to decide, compare and improve campaigns.

Test a creative See capabilities

Predictive accuracy: 95%+
Database: 300,000+ participants
Research: 20+ years

Spring water creatives analyzed by Databrain AI

Focus 87/100

Focus
Cog. Demand
Memory

The brand captures the gaze, but the benefit competes with the background. The recommendation is to raise contrast and move the claim closer to the area of peak fixation.

Optimize with AI recommendations

From a creative asset to a recommendation you can act on.

Databrain AI turns predictive analysis into clear direction: which element to move, which message needs contrast and which version has the most recall potential.

Integrated score across Focus, Cognitive Demand and Memory.
Diagnosis by critical zone of the asset.
Recommendations written for creative and media teams.

Impact Score 8.2/10

Suggested next adjustment
Raise the benefit's hierarchy and cut visual noise around the product to strengthen the brand-message link.

A pipeline built for teams that need to compare many variants without losing methodological rigor.

8 metrics 5 recommendations 4 industry benchmarks

See attention through heatmaps

Identifies what gets looked at, what gets ignored and where the brand gets lost.

Attention maps prioritize logo, product, claim, price and key objects to show whether the asset guides the gaze or scatters it.

HeatmapAOI report

Databrain AI recommendations and heatmaps report

Visibility by area

Calculates the visibility of brand, product, face, claim or any zone that determines the asset's success.

Variant comparison

Detects which version wins on visual clarity, without relying on stated preferences.

Executive read

Turns fixations, dispersion and visual hierarchy into concrete design decisions.

One score. One clear direction.

A shared language across marketing, creative and research.

Every metric appears as a comparable indicator, with context and a recommendation. The direction is simple: launch, adjust, or test more deeply.

Focus 87/100 The ability to capture the gaze in the first seconds.

Cognitive Demand 72/100 Message clarity and the effort required to process it.

Memory 69/100 The likelihood of linking brand and benefit after exposure.

Engagement 76/100 An early signal of the emotional involvement the asset generates, before any media spend.

Three profiles with biometric headsets as the Impact Score visual — Impact Score

Video testing

Reads second by second where the story holds attention and where it loses it.

For spots, reels and audiovisual assets: impact timeline, object detection and brand memory. AI-optimized assets reach up to +64% in brand awareness y +29% in ad recall in direct A/B comparisons. Analyze a video

00:02 detection 00:06 visual peak 00:11 drop-off risk

Quick test

Compare creative variants before putting budget on the street.

The output is built for deciding quickly between creative routes: which variant gets more detection, better comprehension and a higher chance of being remembered.

Variant A

Impact Score 7.4/10 Good brand recognition, weak focus on the benefit.

Variant B

Impact Score 8.8/10 Greater visual concentration and faster reading of the claim.

Variant C

Impact Score 6.6/10 The composition scatters attention and dilutes the logo.

Scientific foundation

Aesthetics change. Rigor does not.

Every read combines models trained on biometric data with researcher validation. Speed to decide, without giving up the science.

Biometric database

More than 300,000 participants and 20 years of eye tracking and brain scanning data back every prediction.

Industry benchmarks

Automatic comparison against category, format and communication objective to put every score in context.

Predictive accuracy

Over 95% accuracy in predicting consumer behavior, validated against real participant data.

Creative action

The analysis ends in concrete recommendations on which element to move, adjust or iterate before launch.