Studio-lit AGRI EEG headset device resting on a clinical monitoring station, stark cool overhead lighting revealing electrode precision, dark background with a faint teal glow from an adjacent screen displaying live waveform data, no people visible
Studio-lit AGRI EEG headset device resting on a clinical monitoring station, stark cool overhead lighting revealing electrode precision, dark background with a faint teal glow from an adjacent screen displaying live waveform data, no people visible
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— EEG-Based Pain Measurement

Pain, Finally Measured.

AGRI is developing a continuous, EEG-based pain index designed to replace subjective self-reporting with objective, standardized neural data. We are in pre-clinical development and seeking research collaborators.

/ The AGRI Index

Four properties no other index delivers

Objective

Continuous

Graded

Non-Invasive

A standardized 0–100 AGRI score enables consistent documentation, inter-clinician communication, and dosing protocols across care settings.

EEG-derived data eliminates the variability of patient self-reporting. The index reflects neural signal, not verbal approximation.

Recurrent indexing streams in real time. Clinicians see the moment pain intensity shifts, not a retrospective point estimate.

EEG-based acquisition requires no needles, no implants, and no procedural risk — compatible with standard clinical monitoring workflows.

Extreme close-up of EEG electrodes placed on a patient scalp in a clinical setting, teal-tinged waveform visible on a monitor screen in the shallow background, surgical suite cool lighting, no face visible, precise and technical framing
Extreme close-up of EEG electrodes placed on a patient scalp in a clinical setting, teal-tinged waveform visible on a monitor screen in the shallow background, surgical suite cool lighting, no face visible, precise and technical framing

Designed for clinical translation to anesthesia suites, ICUs, and pain clinics

AGRI is in active pre-clinical development. We are seeking research collaborators to design and validate our EEG-based pain indexing framework.

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Pain has always been estimated. We are building the evidence to index it.