Vaidya is a clinical reasoning partner for Indian hospitals. AI that thinks alongside your doctors — not instead of them — to catch what gets missed.
The shortage isn't a technology problem — it's an access problem. AI won't replace doctors. But in the 60% of India where doctors aren't available, AI can be the difference between a diagnosis and a missed condition.
Tier 2/3 cities and rural PHCs have essentially zero radiologists. X-rays get shared on WhatsApp as JPEGs for remote interpretation — if at all.
A radiologist reading 80 chest X-rays a day is fighting fatigue, anchoring bias, and time pressure. The error rate climbs with volume.
Models trained on US/EU patient populations have hidden bias on Indian disease prevalence, Indian image quality, Indian equipment. They fail quietly.
Most hospitals outside metros don't run PACS properly. Building for digital-first India misses 60% of the country. Vaidya builds for the real India.
Most medical AI shows you its answer first — training doctors to defer. Vaidya is built on a different principle: the doctor commits independently, the AI analyzes independently, and both are revealed together. Disagreement is the signal.
Upload scans, reports, or notes. Then speak, type, or show your diagnosis via voice, text, or camera. Your assessment is locked before AI sees anything. This prevents anchoring bias from the start.
Assessment Locked · ImmutableMedSAM, nnU-Net, and BiomedCLIP analyze the case in parallel. Each produces an independent assessment. Where they disagree, a synthesizer model reasons through the conflict and produces a weighted verdict with explicit uncertainty flags.
Multi-model Debate Indian Training DataDoctor and AI results appear side by side for the first time. Agreement builds confidence. Disagreement surfaces the cases most likely to contain error — exactly where human review matters most.
Neither saw the other firstWhen the AI disagrees, it explains why — highlighting the specific finding, with the image region marked. The doctor can maintain their verdict (with logged reasoning) or revise. Revising is one click. Maintaining requires choosing a reason.
Full Audit TrailCases above a disagreement threshold, or where AI confidence is below 70%, are automatically flagged for a senior specialist — either in the same hospital or via Vaidya's telemedicine network. Escalation has SLA, not just a flag.
SLA-backed EscalationNo forms. No dropdowns. Just speak your assessment the way you'd dictate a note. Vaidya extracts your diagnosis, confidence level, what you noticed, and what you didn't — all as structured clinical data.
Text, voice, or video — switch mid-conversation. The doctor in a busy district hospital uses voice. The ASHA worker in the field points her phone at a patient's wound. The specialist doing a remote consultation uses video. Same product, same pipeline underneath.
Think out loud. Your spoken assessment is transcribed, structured, and locked in under 15 seconds. Powered by Whisper fine-tuned on Indian English and Hindi medical terminology.
Type a referral note, paste discharge summary text, or use structured input. Works on 2G. Designed for precise documentation and low-bandwidth environments in rural India.
Point your phone at a printed X-ray on a lightbox. Capture a wound, skin lesion, or fundus image. Super-resolution preprocessing corrects for camera capture quality before diagnostic analysis.
Not trained on American hospital data and deployed here. Built ground-up on Indian patient populations, Indian image quality, Indian disease prevalence.
India carries 27% of the global TB burden. Our models are trained on Indian chest X-ray presentations including lower lobe atypical TB — the variant most often missed.
77M diabetics in India, almost no ophthalmologists in rural areas. Fundus camera + Vaidya AI enables non-specialist screening at PHC level.
Remote ECG analysis for 140+ cardiac conditions. Captured in rural clinics, analyzed instantly — report back in under 60 seconds with clinical context.
India has among the highest oral cancer rates globally due to tobacco chewing. Smartphone camera-based screening by ASHA workers — no specialist required.
Fungal infections, leprosy, psoriasis — high burden, massively underdiagnosed. Photo-based triage trained on Indian skin tones and Indian disease patterns.
Real-time guidance for non-specialist ultrasound operators. Detects fetal anomalies and flags cases for specialist review — deployable by trained ANM workers.
A single model gives you a single answer. Three specialized models that debate each other — and must resolve disagreement explicitly — give you calibrated uncertainty and catch each other's blind spots.
All model weights trained and validated on Indian patient data. Debate transcript logged for every case — your CDSCO compliance record, automatically.
Not retrofitted for compliance. Designed for it from the ground up — CDSCO medical device pathway, DPDP Act 2023, and the audit requirements that come with clinical AI.
AI diagnostic software classified as SaMD under MDR 2017. Our clinical validation is structured for CDSCO submission from day one — Indian patient data, Indian validation cohorts.
Health data classified as sensitive personal data. Full de-identification pipeline, DICOM metadata scrubbing, consent management in local languages, right to withdraw.
Every doctor assessment, AI verdict, disagreement, revision, and escalation — logged with timestamp, user, and reasoning. The complete clinical reasoning chain, not just the output.
All training data collected through hospital research partnerships with formal ethics clearance. Prospective clinical study design — the same data trains our models and supports regulatory submission.
We're partnering with 10 hospitals in our first cohort. Free deployment. Joint clinical study. Your radiologists get AI-assisted diagnosis, we get the validation data that makes Vaidya better for all of India.
For hospitals, diagnostic chains, and PHC networks. No commitment required.