Platform

Cognitive features and endpoints that earn trust

Validate products, features, and research endpoints on a credible longitudinal measurement backbone.

Let's talk

Let's talk

About

Designed for teams building technology and science where robustness, interpretability, and change sensitivity matter.

Move beyond one-off assessments with longitudinal brain monitoring that adds objective, repeatable insight across every visit, strengthening interpretation and confidence over time.

Let's talk

Let's talk

Let's talk

All cognitive metrics are measured vs. an individual’s baseline using analytical models.

4 Wednesday

12:51 AM

Subjects

Programs

Cohorts

Exports

Settings

Overview

Confidence: Moderate

Stability: High (ICC 0.78)

Quality: Good

0.15

0.10

0.05

0.00

-0.05

-0.10

-0.15

-0.20

-0.25

Delta from Baseline

Jul 15

Aug 12

Sep 8

Oct 5

Nov 18

Observed change: Mild decrease vs baseline

Confidence: Moderate (5 data points, good quality)

Sensitivity: This metric is sensitive to sleep deprivation, caffeine intake, and task engagement

Build longitudinal, within-person baselines

See what’s ‘normal’ for each person and when something is meaningfully different.

Integrate the data you already use

Build an individual sensitivity profile

All cognitive metrics are measured vs. an individual’s baseline using analytical models.

4 Wednesday

12:51 AM

Overview

Observed change: Mild decrease vs baseline

Confidence: Moderate (5 data points, good quality)

Sensitivity: This metric is sensitive to sleep deprivation, caffeine intake, and task engagement

Build longitudinal, within-person baselines

See what’s ‘normal’ for each person and when something is meaningfully different.

Integrate the data you already use

Build an individual sensitivity profile

All cognitive metrics are measured vs. an individual’s baseline using analytical models.

4 Wednesday

12:51 AM

Subjects

Programs

Cohorts

Exports

Settings

Overview

Confidence: Moderate

Stability: High (ICC 0.78)

Quality: Good

Observed change: Mild decrease vs baseline

Confidence: Moderate (5 data points, good quality)

Sensitivity: This metric is sensitive to sleep deprivation, caffeine intake, and task engagement

Build longitudinal, within-person baselines

See what’s ‘normal’ for each person and when something is meaningfully different.

Integrate the data you already use

Build an individual sensitivity profile

Solution

What developers and researchers can do with Connectome

Connectome provides a trusted longitudinal measurement layer that sits above devices and protocols, enabling robust evaluation of cognitive change without diagnostic or clinical claims.

Validate features and endpoints

Separate meaningful cognitive change from expected within-person variability, so performance, protocol effects, or interventions can be assessed with confidence across repeated measurement.

Tune products, models, and protocols

Study how cognition evolves across cohorts, conditions, and contexts to inform iteration, refinement, and design decisions.

Move beyond behavioural proxies

Complement behavioural and wearable signals with brain-grounded measurement, providing a physiological reference for longitudinal evaluation of attention, load, stability, and recovery longitudinally.

Generate study-ready evidence

Produce standardised, repeatable outputs with clear confidence and provenance.

We're bringing the science of brain connectivity out of the lab and into people's lives, so anyone can understand how their brain works, and how to support it.

Rufus Mitchell-Heggs

PhD / CSO at Connectome

Integration

Study cognition over time across people, products, and contexts

Move beyond snapshot studies toward an understanding of how cognition changes across repeated exposure, real-world conditions, and time. Connectome supports longitudinal analysis across:

  • Individuals and cohorts

  • Product iterations and feature releases

  • Contextual factors such as sleep, travel, workload, or task demands

All interpreted against each individual’s own baseline, with explicit confidence and clear “no signal” states.

Platform

Cognitive features and endpoints that earn trust

Validate products, features, and research endpoints on a credible longitudinal measurement backbone.

Let's talk

Let's talk

About

Designed for teams building technology and science where robustness, interpretability, and change sensitivity matter.

Move beyond one-off assessments with longitudinal brain monitoring that adds objective, repeatable insight across every visit, strengthening interpretation and confidence over time.

Let's talk

Let's talk

Let's talk

All cognitive metrics are measured vs. an individual’s baseline using analytical models.

4 Wednesday

12:51 AM

Subjects

Programs

Cohorts

Exports

Settings

Overview

Confidence: Moderate

Stability: High (ICC 0.78)

Quality: Good

0.15

0.10

0.05

0.00

-0.05

-0.10

-0.15

-0.20

-0.25

Delta from Baseline

Jul 15

Aug 12

Sep 8

Oct 5

Nov 18

Observed change: Mild decrease vs baseline

Confidence: Moderate (5 data points, good quality)

Sensitivity: This metric is sensitive to sleep deprivation, caffeine intake, and task engagement

Build longitudinal, within-person baselines

See what’s ‘normal’ for each person and when something is meaningfully different.

Integrate the data you already use

Build an individual sensitivity profile

All cognitive metrics are measured vs. an individual’s baseline using analytical models.

4 Wednesday

12:51 AM

Overview

Observed change: Mild decrease vs baseline

Confidence: Moderate (5 data points, good quality)

Sensitivity: This metric is sensitive to sleep deprivation, caffeine intake, and task engagement

Build longitudinal, within-person baselines

See what’s ‘normal’ for each person and when something is meaningfully different.

Integrate the data you already use

Build an individual sensitivity profile

All cognitive metrics are measured vs. an individual’s baseline using analytical models.

4 Wednesday

12:51 AM

Subjects

Programs

Cohorts

Exports

Settings

Overview

Confidence: Moderate

Stability: High (ICC 0.78)

Quality: Good

Observed change: Mild decrease vs baseline

Confidence: Moderate (5 data points, good quality)

Sensitivity: This metric is sensitive to sleep deprivation, caffeine intake, and task engagement

Build longitudinal, within-person baselines

See what’s ‘normal’ for each person and when something is meaningfully different.

Integrate the data you already use

Build an individual sensitivity profile

Solution

What developers and researchers can do with Connectome

Connectome provides a trusted longitudinal measurement layer that sits above devices and protocols, enabling robust evaluation of cognitive change without diagnostic or clinical claims.

Validate features and endpoints

Separate meaningful cognitive change from expected within-person variability, so performance, protocol effects, or interventions can be assessed with confidence across repeated measurement.

Tune products, models, and protocols

Study how cognition evolves across cohorts, conditions, and contexts to inform iteration, refinement, and design decisions.

Move beyond behavioural proxies

Complement behavioural and wearable signals with brain-grounded measurement, providing a physiological reference for longitudinal evaluation of attention, load, stability, and recovery longitudinally.

Generate study-ready evidence

Produce standardised, repeatable outputs with clear confidence and provenance.

We're bringing the science of brain connectivity out of the lab and into people's lives, so anyone can understand how their brain works, and how to support it.

Rufus Mitchell-Heggs

PhD / CSO at Connectome

Integration

Study cognition over time across people, products, and contexts

Move beyond snapshot studies toward an understanding of how cognition changes across repeated exposure, real-world conditions, and time. Connectome supports longitudinal analysis across:

  • Individuals and cohorts

  • Product iterations and feature releases

  • Contextual factors such as sleep, travel, workload, or task demands

All interpreted against each individual’s own baseline, with explicit confidence and clear “no signal” states.