Methodology · Data provenance
How we capture the data behind the model.
From the consented people who provide the signal to the synthetic audiences you simulate against, every stage of our data pipeline has a guardrail. Here is the full path, with nothing about the model itself exposed.
01 · Source
Consented data, documented at source
Every neurophysiological and behavioural signal is collected under informed, opt-in consent. Participants are briefed on use and retain the right to withdraw, and we record provenance for each data stream.
No data without consent02 · Train
The model is trained only in the lab
The neuroscience model is trained exclusively with participants who consented to provide the data, and studied across Latin, English, and US populations so it generalises across more than one market.
Supervised by scientists03 · Calibrate
Calibrated against a 300,000-person cohort
Calibration runs through a tracking remote across a cohort of 300,000 people who agreed to take part. The scale and spread let us cross-border screen the algorithms and catch regional divergence before anything ships.
Cross-border screening04 · Validate
Checked for bias across markets
Predictions are evaluated for systematic error across age, gender, and region. Where a market diverges, the discrepancy is corrected before the calibration is promoted.
Fairness checks before release05 · Generalise
Translated into synthetic audiences
The calibrated parameters set the rules that 100,000 synthetic audience profiles follow in every simulation. Each is a statistical agent fitted to population behaviour, with no link to a real, identifiable person.
No real individuals modelledHow participants are recruited, consented & compensated
Recruitment
Sourced through a vetted research panel
Lab and calibration participants are recruited through a vetted external research-participant platform: a large, pre-screened pool where people opt in to take part in studies. We do not cold-source, scrape, or repurpose customer data to build the cohort, and participants are matched to the demographics a study requires.
Consent & ethics
Voluntary, informed, and ethics-reviewed
Participation is voluntary and based on informed, opt-in consent: people see what a study involves before joining, are told their neurophysiological and behavioural responses are used to research and calibrate North AI's audience models, and can withdraw at any time. The platform operates an ethics framework for online research, and studies follow its participant-protection standards.
Compensation
Paid fairly for their time
Participants are paid for their time at or above the platform's enforced fair-pay minimum. Compensation is never contingent on the responses they give, so there is no incentive to answer in a particular way.
Cross-border by design
The 300,000-person calibration cohort spans Latin, English, and US populations, so we can run the same algorithm across markets and detect divergence rather than assume one region generalises to another.
Bring your own cohort
If your audience isn't fully represented, we can onboard an additional cohort for your use case and fold it into calibration, so the simulation is screened against the people you care about.
Representativeness you can inspect
Our live audience map shows how many consented participants are available in each country, broken down by age and gender. You can see the real composition behind a simulation, and where a market is thin, before you rely on it. Explore the audience map →
Reviewing North AI for your organisation?
We can walk procurement, legal, and security teams through our data provenance, controls, and documentation, and onboard a custom cohort if you need one.