where decisions already happen

Put predictive attention data where your media decisions already happen.

AttentionAI turns creative into structured, predictive attention datasets that integrate directly into your planning tools, reporting systems, creative workflows and AI-enabled environments.

Whether via API or MCP, AttentionAI helps teams move beyond one-off reports and make human attention a native input into how creative and media decisions are made.

  • REST API
  • Webhooks
  • MCP / agentic
  • Real human attention
attentionai · bashlive
POST /creatives201 CreatedGET /…/synthetic_audienceWebhook event
1# register a creative for attention analysis
2curl -X POST https://api.attentionai.amplified.co/api/v1/creatives \
3 -H "Authorization: Bearer $AMP_KEY" \
4 -H "Content-Type: application/json" \
5 -d '{
6 "downloadableUrl": "https://cdn.acme.co/summer_v3.mp4",
7 "webhookUrl": "https://app.acme.co/hooks/attention"
8 }'
attention dataset · ready
73.4/100
+12 vs format benchmark
78
Hook
65
Hold
active attentionpassive attention
attention at scale

Built for teams who need attention at scale

For brands, agencies, platforms and analytics teams that want to operationalise attention across high-volume workflows.

Upload or register creative, run predictive attention analysis, and receive structured outputs back into the systems your teams already use - no manual reporting layer required. The API supports programmatic upload, rapid-turnaround datasets and direct integration.

use attentionAI to

  • Test large volumes of creative before launch
  • Compare performance across platforms and formats
  • Feed attention data into planning and reporting tools
  • Support creative optimisation workflows
  • Integrate attention into MMM and forecasting
  • Build custom attention-led decision frameworks

ATTENTION DATA · INTO EVERY SYSTEM

Your creative

mp4 · mov · public url

AttentionAI engine

predictive attention model

Via API

rest · json · webhooks

Via MCP

agentic / ai tools

lands inside your stack

Planning toolsDashboardsMMM & forecastingCreative pipelinesAI assistants
two ways in

Two ways to integrate AttentionAI

Pick the path that matches how your teams actually build, whether it’s structured data inside your own systems, or attention made available to AI-enabled workflows.

01

API integration

For teams that want structured attention data directly inside their own systems. Upload or register video assets or URLs, trigger predictive analysis, and receive structured outputs consumed by your platforms, dashboards and internal models.

best for

  • Enterprise media workflows
  • High-volume creative testing
  • Internal reporting environments
  • Marketing mix modelling
  • Automated creative optimisation
  • Custom planning tools

02

MCP integration

MCP integration allows AttentionAI outputs to be accessed by AI-powered environments, helping teams bring predictive attention into automated workflows, decision support systems and internal assistants.

best for

  • AI-enabled planning workflows
  • Creative review agents
  • Automated insight generation
  • Internal media decision tools
  • Teams exploring agentic optimisation
three steps

How it works

From creative to a complete attention dataset built to run at production scale, asynchronously.

STEP 1

Upload or register creative

Send a file or a public URL. Get back a creative ID, prepared for analysis.

POST /creatives

STEP 2

AttentionAI processes the asset

Analysis runs asynchronously. Poll for status or receive a webhook on completion.

async · webhook

STEP 3

Receive a complete dataset

A rich, ad-specific attention dataset, ready to plug into your systems.

GET /…/synthetic_audience
the output

What AttentionAI delivers back

Every asset generates a structured dataset designed to support both creative and media decisions.

Attention seconds, including active and passive attention
Second-by-second attention decay curves
Attention score
Benchmark comparisons against format norms
Hook & Hold performance
Structured JSON / API response outputs

Designed to plug straight into planning tools, reporting dashboards and internal models.

creative_summer_v3.mp4

15s · 16:9 · facebook feed

JSON ready

Attention score

73.4

Active sec

4.7s

Passive sec

1.9s

attention decay · 30s

activepassive
reusable by design

One creative. Every relevant platform. Every audience.

AttentionAI detects the creative’s aspect ratio and duration, then returns attention data for matching platforms and formats. Each upload can also be explored against a modelled audience of 20,000 viewers, helping teams understand how attention is likely to differ across audiences and media environments.

one upload becomes a reusable dataset across

PlatformsFormatsDevicesDemographicsCreative comparisonsPlanning scenarios

modelled audience

Attention score

18–24
64
25–34
78
35–44
71
45–54
58
55+
47
in the wild

Where AttentionAI can be used

Use AttentionAI to test creatives at scale, compare assets, identify stronger executions and feed results back into creative pipelines. The API supports use cases such as batch testing, auto-selecting stronger creative and feeding results into creative workflows.

Creative workflows

Test creatives at scale, compare assets, identify stronger executions and feed results back into creative pipelines.

  • Compare campaign variants
  • See which creative earns attention fastest
  • Understand where attention drops
  • Improve hooks, pacing and branded moments
  • Prioritise assets before spend is committed

Media workflows

Connect creative performance to media decisions, from platform selection to spend.

  • Link creative quality to platform and format
  • Adjust spend based on predicted attention
  • Build attention-weighted planning inputs
  • Find formats where creative works best
  • Support channel and placement calls

Analytics & modelling

Use attention as an input into advanced analytics and decision systems.

  • Feed attention into MMM and econometrics
  • Add attentive seconds into forecasting
  • Build custom optimisation models
  • Standardise attention across channels
  • Create your own performance framework

AI & agentic workflows

Use MCP to make attention available inside AI-enabled workflows.

  • Ask an assistant to compare creative attention
  • Generate attention-led recommendations
  • Pull attention into planning agents
  • Explain results for creative and media teams
  • Use attention alongside reach, frequency, cost
real-world coverage

Designed for real-world media environments

AttentionAI supports a wide range of digital and video formats today, with more media environments on the way.

live now · digital & video

Facebook
Instagram
TikTok
Snapchat
YouTube
Pinterest
General web
VOD / BVOD

coming soon

SVODAVODLinear TVStatic displayCinemaOutdoor
trained on real behaviour

Built on real human attention, not proxy metrics.

AttentionAI is trained on real human attention signals and grounded in observed behaviour, not viewability layers or proxy assumptions. This foundation is designed to improve accuracy, commercial reliability and scalable decision-making. That means the outputs are built to help teams understand not just whether an ad was delivered, but how audiences are likely to pay attention to it across media.

A continuous signal

not a one-off report

A scalable dataset

not a static output

An embedded capability

not a standalone tool

for both sides of the team

Built for technical and non-technical teams

Technically robust under the hood, practical for commercial teams on top.

technical characteristics

REST API architectureJSON request / responseAsync processingWebhook supportCloud-hosted infrastructure
attentionai · bashlive
POST /creatives201 CreatedGET /…/synthetic_audienceWebhook event
1# register a creative for attention analysis
2curl -X POST https://api.attentionai.amplified.co/api/v1/creatives \
3 -H "Authorization: Bearer $AMP_KEY" \
4 -H "Content-Type: application/json" \
5 -d '{
6 "downloadableUrl": "https://cdn.acme.co/summer_v3.mp4",
7 "webhookUrl": "https://app.acme.co/hooks/attention"
8 }'
make attention a decision layer

Ready to integrate attention into your workflow?

Whether you’re building a planning tool, scaling creative testing, feeding MMMs, developing AI-enabled workflows or creating a custom optimisation model, AttentionAI can help turn predictive attention into a practical decision layer.