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The human ground truth for AI media

AI now plans, buys, and grades its own media. Beatgrid is the independent human signal that should respond to real person-level cross-media ad exposure as a continuous calibration layer. (now in closed testing)

 

Independent proof of what every ad, every channel delivered.

 True single-source cross-media measurement — every ad measured on the same real people across all CTV, linear TV, BVOD, YouTube, social, audio, and OOH. 

 

The Human Ground Truth for AI Media

AI now plans, buys, and grades its own media. Beatgrid is the independent human signal that should respond to real person-level cross-media ad exposure as a continuous calibration layer. (now in closed testing)

The Problem

AI without ground truth makes bad decisions — faster

Today's media AI is the most capable it's ever been — planning, bidding, and optimising across millions of impressions in milliseconds. But it learns from the wrong teacher: bid-streams, ad-server logs, and the platforms' own self-reports — the same systems whose biases it was built to remove. It optimises against what was served, never what a human was exposed to. And speed multiplies the error.

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The foundation

220
K

Active human panellists across 6 markets

1
M+

Ads measured per year

61
M+

Human-Ad impact signals

The Solution

The independent feedback loop that breaks the optimisation echo chamber

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Advertising AI Calibration

Real human exposure is the ground truth for AI media planning & buying 

c1

Clean-room native

Built for clean-room delivery — no raw data movement or PII exchange.

c3

MMM Calibration card

The independent feedback loop that breaks the optimisation echo chamber.

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No Integration Needed

The only ground truth that needs no media platform permission

Most solutions need the platforms' permission to measure inside a walled garden, require licensing its data, or spend years in an integration process, only to get a cross-platform picture stitched from sources someone else owns and controls.


Beatgrid can measure the ad itself: encode it once, and we pick it up wherever it plays, collecting millions of real-world human media behaviour, campaign outcomes, and signals from one panel of real people across six markets. No platform's permission, because no 3rd-aprty data.

How It Works

Data infrastructure for AI-driven media buying

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Behavioural feedback signal

Real human exposure on real people, captured by hybrid ACR. No modelling, no bid-stream inference. 

Clean-room native delivery

UID2 and RampID resolution; Snowflake, AWS Clean Rooms, Habu, or InfoSum. No raw data movement. 

RLHF for media AI

Reinforcement Learning from Human Feedback (RLHF) that calibrates Bayesian MMM and AI media-buying models.

Model evaluation

Independent verification of what AI buying systems actually delivered, on real people across every screen. 

Always-on signal streams

Five continuous data feeds: cross-media exposure, OOH proximity, retail footfall, omnibus brand tracking, and app usage. 

Closed-loop calibration

Automated weekly feedback between AI optimisation and observed reality. Drift percentage per dimension. 

The Data Infrastructure (now in closed testing)

Three layers of human-feedback infrastructure. One continuous data product.

Always-on, identity-resolved human-exposure data.

  • ACR cross-media exposure
  • OOH proximity
  • Retail footfall
  • Omnibus brand tracking
  • App usage
  • UID2 + RampID resolved
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AI buying systems - animated

Independent verification of what AI buying systems actually delivered

  • Drift percentage per dimension
  • Predicted vs observed deltas
  • Calibration recommendations
  • Weekly automated updates

Plug human ground truth into systems you already run on

  • Snowflake Secure Share
  • AWS Clean Rooms, Habu, InfoSum
  • API access
  • Downloadable datasets
  • Benchmark comparisons
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Use Cases

How do your models perform differently with human ground truth?

B1

Cross-platform Frequency Calibration

 True cross-platform frequency capping is an illusion. Each DSP controls only what its own platform serves. Beatgrid AI delivers true, unduplicated frequency across platforms, calibrating each DSP's frequency per segment.

B2

Build MMM priors

Replace modelled priors with real exposure-to-outcome data, measured on the same people rather than stitched from separate panels. Tighter posteriors, faster modelling, and a number your finance team can defend.

B3

Detect AI drift

Catch when your agentic planning and buying starts optimising against its own biases. A continuous stream of outcome signals, measured weekly per dimension, corrects the drift before it costs a quarter of your budget.

Ready to elevate your Media AI business?

Documentation

Documentation, methodology papers, and integration guides for the AI buying stack.

Resource 1

Bayesian MMM Priors — A Practical Guide

Resrouce 2

Clean-Room Integration Guide — UID2, RampID, Snowflake, AWS Clean Rooms, Habu

Resource 3

Cross-Media Reach Deduplication — Methodology

Resource 4

AI Calibration Loop — Architecture Overview

Resource 5

Human-Verified Exposure — Methodology Whitepaper

Frequently asked questions

What is Beatgrid AI?

The deterministic human-exposure dataset built to calibrate avertsing AI media planning and buying, MMM, and incrementality — continuous, identity-resolved, single-source. Now in closed testing, delivered into your clean room as the independent ground truth your models verify against.

What does “ground truth for AI media” mean?

Ground truth is real human exposure measured at person level, observed deterministically across every channel — used to verify what AI buying, MMM, and planning systems are actually delivering. It is independent of the platforms whose performance is being measured. 

How is Beatgrid AI different from Beatgrid's campaign measurement?

Campaign measurement reports outcomes per campaign. Beatgrid AI delivers the same panel and ACR as a continuous, identity-resolved data feed into your infrastructure — to calibrate AI buying, supply MMM priors, and close feedback loops. This delivery model is in closed testing now, launching H1 2027

What is the calibration pilot?

 A closed-testing engagement where your data team and Beatgrid co-create the business case for an ongoing partnership. The deliverable is a customer-validated ROI model — not a data-sample drop. Pilot slots are limited ahead of launch.

How is the data delivered?

 Via Snowflake Secure Data Share, AWS Clean Rooms, Habu, or InfoSum. Your models access the dataset as a local table inside your own infrastructure. No raw data movement, no PII exchange 

Does Beatgrid AI integrate with our MMM?

Outputs deliver as deterministic priors for Bayesian MMM, compatible with Meridian, Robyn, and most enterprise MMM platforms — replacing modelled priors with real, observed exposure. 

What identity resolution does Beatgrid support?

UID2 and RampID, hashed at the panel level. Identity resolution happens inside your clean room — no PII is ever exchanged between Beatgrid and the buyer. 

How fresh is the data?

Designed for continuous delivery — weekly or daily cadence by tier — across cross-media exposure, OOH proximity, retail footfall, omnibus brand tracking, and app usage. Available to pilot partners now; general availability H1 2027

Does the data enable per-person cross-platform CTV frequency capping?

Beatgrid is a single-source panel, so it calibrates cross-platform frequency at the audience-segment level, with confidence intervals — not per-identity. We don't cap the individual impression; we measure true unduplicated exposure across platforms and linear, and correct the frequency number your buying engine caps against. Capping executes inside a platform's delivery path; calibration is the independent cross-channel signal that tells it what to cap to.

What is the panel size and coverage?

 Approximately 220,000 active metering panellists across six markets with extraordinarily rich and accurate actual media behaviour data. Human data across the United States, United Kingdom, Australia, Germany, Canada, and India — powered by 5.8 million cumulative app installs of Beatgrid's own consumer apps Media Rewards and Jagger. Each market panel is demographically weighted. 

Is Beatgrid neutral across the AI ecosystem?

 Yes. Beatgrid sells to all agency holding companies, DSPs, advertisers, and MMM providers on identical terms. No single party holds strategic investment or category exclusivity — neutrality is the structural condition that keeps the data valuable to every buyer simultaneously. 

Is the data privacy-compliant?

 Yes — fully GDPR, CCPA, ESOMAR, and MRC compliant. No audio is ever stored: the system captures a mathematical fingerprint, not a recording. Every panellist provides double opt-in consent with full withdrawal rights.