One Cascade.
Every Specialty.
QuantVeda builds clinical AI that reasons the way medicine is practised: knowledge-base-first, with every score computed deterministically by code and every recommendation placed in front of a licensed clinician. Thirty-eight Wave-1 applications reason clinically across specialties today — from general medicine to cardiology, oncology, rare disease, and antimicrobial stewardship.
Clinical reasoning, in production
Flagship applications from the 38-product Wave-1 portfolio, live on quantveda.com today.
Eleven flagship applications shown · 38 products built in Wave 1.
AI Physician Pro
Live192 decision trees with an anatomical body-map picker, type-ahead search, and four Bayesian engines.
Open application →AI Physician
LiveAI Physician clinical application — open the app for details.
Open application →HRIDAYA
LiveAI Cardiologist: 201 clinical entries across 31 sheets covering 99% of board-level cardiology.
Open application →ARJUN
LiveAI Oncologist: 185 cancers, 9 OMNIOME multi-omics layers, 9 clinical steps — predictive preventive oncology.
Open application →OMNIOME
LiveClinical intelligence platform for precision genomic medicine, pharmacogenomics, and health analytics.
Open application →KSHEMA
LiveAI Rare Disease Navigator: 7,003 rare diseases, 7 intelligence layers, 12-step clinical pipeline.
Open application →QDDA
LiveQuantum drug discovery architecture — disease to target ID, molecular design, and clinical-grade validation.
Open application →CardioPredict
LiveAI cardiovascular risk prediction — CardioPredict v5.0.
Open application →NEEL
LiveAI general surgery assistant powered by 18 knowledge bases.
Open application →KAVACH
LiveAI-powered antimicrobial stewardship and resistance surveillance platform.
Open application →SOBHA
LiveAI Gynaecologist — clinical decision support for obstetrics & gynaecology.
Open application →From reasoning to continuous care
Wave 1 answered: can we reason clinically at population scale? Wave 2 answers a different question: can we hold one patient's state continuously, act on it across every setting, and prove it changed the outcome? A Wave-1 product is done when it reasons correctly; a Wave-2 product is done when it writes to shared state, closes a loop, and emits evidence.
In active development · Not available for clinical usePrinciples that do not bend
KB-first
Knowledge bases are authored, clinically reviewed, and frozen before the engines that consume them are built.
Deterministic scores, model narrative
Scores are computed by code. Narratives are generated by the model. These never swap — a model never produces a risk score, a dose, or a probability.
Clinician-in-the-loop
Applications support licensed clinicians; recommendations are reviewed by a human, never issued autonomously to a patient.
Provenance on every assertion
Every clinical claim resolves to a knowledge-base id and version. Unattributable output is suppressed.