The population your study is missing.
Explore real-world brain data across populations, diagnoses, devices, and study contexts—before, during, and after a trial.
Reference scale
Population context, ready for analysis.
A harmonized foundation of labeled brain-wave data and longitudinal clinical context—built to answer a specific development question, not to sell raw patient data.
500K+
brain scans
Real-world EEG reference scale
200M
medical notes
Longitudinal clinical context
20
device types
Heterogeneous source coverage
70K+
features per scan
Precomputed for analysis
Real patient data is never sold raw. Partners receive approved insights, statistical summaries, and model outputs for the agreed use case.
Across development
Use the same reference layer at three different decisions.
The question changes across the program. The underlying population context stays connected.
Before the trial
Discover and design
Explore population distributions, assess feasibility, and compare candidate cohorts before locking the protocol.
During the trial
Measure and contextualize
Compare a sponsor cohort with relevant reference populations and investigate treatment-effect or responder questions.
After the trial
Validate and extend
Test whether a finding remains robust across populations, devices, and study contexts.
Data integrity
Heterogeneous inputs. One analyzable reference layer.
Datahub harmonizes source studies and metadata so teams can ask population-level questions without pretending every dataset was collected the same way.
Labeled context
Diagnoses, patient history, and study metadata connected to brain-wave recordings.
Cohort definition
Filter by population, diagnosis, device, and study context for the question at hand.
Multi-region coverage
Source data spans the United States, Europe, the Middle East, and Asia.
Controlled access
Approved statistical outputs and model artifacts—not a raw-data marketplace.
Evidence in practice
Move from a reference population to a development decision.
See how Brainify.AI has used population data and AI-based biomarkers in real pharmaceutical research programs.
Start with your question
Start with the population your program needs.
Tell us the indication, phase, study design, and decision you need to support. We will recommend the first Datahub analysis.