Identify the right patient.
For the right drug.
Every time.
KolateAI's agentic AI platform predicts and simulates individual patient outcomes: drug response, adverse events, and disease risk. It works quickly, accurately, and at scale, so your team can target the best-fit patients instead of guessing.
Resident company of Johnson & Johnson Innovation, JLABS @ NYC, and backed by
A unified agentic AI platform for patient-level outcome prediction & simulation.
KolateAI turns fragmented patient-level data (proprietary, external, real-world, and trial) into individual outcome predictions and digital twins, orchestrated by disease-specific models.
Aggregates Multi-Modal Data
Proprietary, external, and synthetic real-world & trial data: structured, notes, and imaging.
Integrates Patient History
Builds a full longitudinal treatment narrative and trajectory per patient.
Orchestrates Disease-Specific Models
Trains and auto-selects the best-fit model per therapeutic area using KCV, a composite score balancing accuracy, F1, AUC, and explainability.
Generates Digital Twins
Simulates each patient under alternative therapies for head-to-head, no-new-trial-needed comparisons.
KolateAI Predict
Targeted patient-level prediction of drug response, adverse events, and disease risk, before a trial starts or a prescription is written.
KolateAI Compare
Emulated head-to-head comparison of alternative therapies using synthetic control arms, generating RWE without a new prospective trial.
KolateAI Co-pilot
An interactive assistant for study physicians & scientific staff to query predictions, study actuals, and protocol documentation in real time.
A quick look inside the platform.
Three screens from the actual KolateAI workspace: cohort building, best-fit prediction, and therapy comparison.
Define a cohort in minutes
Explicit inclusion/exclusion criteria, live cohort size, and descriptive stats, with no data engineering required.
Get a best-fit prediction
The best model is pre-selected automatically: cohort- and patient-level response, ready to filter and export.
Compare therapies in-silico
Digital twins weigh your target therapy against alternatives, for one patient or a whole cohort.
Validated across therapeutic areas.
High-level results from KolateAI work samples and pilot studies with design partners. Details are in full on the Studies page.
Atopic Dermatitis Therapy Response
Identified treatment-resistant patients predicted not to respond to TCS or Dupilumab, before they were prescribed.
CAR T-Cell Therapy Comparison
Synthetically compared two CD19-directed CAR T-cell therapies for relapsed/refractory Large B-Cell Lymphoma on a common patient group.
What design partners are saying.
"We learnt something new about our drug: that it directly benefited certain metabolic syndrome patients, while making the condition worse in others, and are now able to target the right patients for our upcoming clinical trial."
"KolateAI made it simple for us to generate RWE comparing our new drug with prior alternatives, using their head-to-head therapy comparison tool."
Ready to bring precision medicine to your program?
Talk to us about a proof-of-concept for your therapeutic area.