# Medows

> Medows is an AI-assisted clinical workspace for the doctor on rounds. It holds the patient list while doctors do the work — vitals between beds, AI answers grounded in the actual patient on screen, and handover messages sent over WhatsApp.

Medows is built for junior doctors, residents (PGTs), and ward-based clinicians in busy hospitals — particularly the heavy-admission shifts where a single doctor may carry 20–30 patients overnight. It is a personal workspace, not an EHR: patient data is scoped to a single sign-in and not shared across the hospital.

The product was designed alongside doctors in Indian government and private hospitals. It is free for individual clinicians.

## Core pages
- [Home — what Medows is](https://www.medows.ai/): Hero, three core capabilities (Track, Consult, Hand off), and contact.
- [Blog — notes from the ward](https://www.medows.ai/blog): Essays on clinical AI, ward workflow, residency, case studies, and the future of doctor-side software, written by the Medows team and the doctors we build with.
- [Privacy](https://www.medows.ai/privacy): How patient data is stored and isolated per sign-in.
- [Terms](https://www.medows.ai/terms): Terms of use for the personal workspace.

## Recent posts
- [FDA Cleared 1,357 AI Devices. Only 3 Proven.](https://www.medows.ai/blog/fda-cleared-1-357-ai-devices-only-3-proven): FDA cleared 1,357 AI medical devices. A new study found only 3 were tested on whether patients actually got better.
- [The AI Scribe Rollout That Actually Stuck](https://www.medows.ai/blog/the-ai-scribe-rollout-that-actually-stuck): Cleveland Clinic put an AI scribe in front of 4,000+ clinicians in 16 weeks. The lesson wasn't the model. It was the rollout.
- [Diagnostic AI's 95% Accuracy Problem](https://www.medows.ai/blog/diagnostic-ai-s-95-accuracy-problem): New research: data leakage inflates AI schizophrenia-detection accuracy by up to 30%, exposing why near-perfect diagnostic AI claims deserve real scrutiny.
- [The CSF that did not fit](https://www.medows.ai/blog/the-csf-that-did-not-fit): A CSF report with 920 cells and 92% polymorphs and a glucose and protein that both read normal. What antibiotics can and can't explain before the next lumbar puncture.
- [FDA Will Grade AI Like It Grades Doctors](https://www.medows.ai/blog/fda-will-grade-ai-like-it-grades-doctors): The FDA wants feedback on grading generative AI medical devices the way it evaluates physicians: by competency, not just code.
- [Diagnostic AI Finally Gets a Rulebook](https://www.medows.ai/blog/diagnostic-ai-finally-gets-a-rulebook): Twelve US health systems and Aidoc formed a consortium to govern diagnostic AI, betting that shared standards beat point solutions.
- [Clinical AI's Real Danger: What It Skips](https://www.medows.ai/blog/clinical-ai-s-real-danger-what-it-skips): The largest clinical AI safety study yet found most severe errors are omissions, not wrong answers, and purpose-built tools beat general chatbots.
- [Hospital AI Pilots Work. Scaling Doesn't.](https://www.medows.ai/blog/hospital-ai-pilots-work-scaling-doesn-t): A new survey finds EHR integration, not clinician trust, is the real reason clinical AI pilots stall before they scale.
- [Before AI Hits the Ward, Doctors Test It](https://www.medows.ai/blog/before-ai-hits-the-ward-doctors-test-it): UnityPoint has 60 physicians pressure-test AI tools before rollout, not after. What that says about verifiable clinical AI.
- [Clinical AI Explanations Can Mislead Beginners](https://www.medows.ai/blog/clinical-ai-explanations-can-mislead-beginners): A Nature Medicine study finds AI diagnostic explanations boost novice confidence even when wrong, while trained clinicians barely benefit.
- [AI Scribe or Medical Device? The UK Decides](https://www.medows.ai/blog/ai-scribe-or-medical-device-the-uk-decides): The MHRA just clarified when an AI scribe counts as a medical device in the NHS, and what it means for the doctors relying on one.
- [Which AI Can a Doctor Actually Trust?](https://www.medows.ai/blog/which-ai-can-a-doctor-actually-trust): A new leaderboard scores 18 AI models on medical safety. The general chatbots doctors reach for aren't the safest ones in the room.
- [AI Finds Bias in Half of Pregnancy Notes](https://www.medows.ai/blog/ai-finds-bias-in-half-of-pregnancy-notes): A new AI analysis of 640,000+ obstetric notes found stigmatizing language in 47% of pregnancies, worse for Black and less-educated patients.
- [AI fixed the clinical note. Not the ward round.](https://www.medows.ai/blog/ai-fixed-the-clinical-note-not-the-ward-round): Ambient AI scribes cut documentation time and burnout, and that is real. But the note was never the hard part of a shift. The ward round is the frontier.
- [India moved to ban paraquat. The casualty doctor's problem does not end today.](https://www.medows.ai/blog/india-moved-to-ban-paraquat-the-casualty-doctor-s-problem-does-not-end-today): India issued a draft order to ban paraquat on 13 July. It is not final yet, and the patient who walks into casualty tonight still has no antidote.
- [Medows is launching on Product Hunt](https://www.medows.ai/blog/medows-is-launching-on-product-hunt): Medows is launching on Product Hunt on July 16: the first AI clinical workspace built for the individual doctor. Walk a real shift in our no-sign-up demo.
- [Why Medows Is the First AI Clinical Workspace](https://www.medows.ai/blog/why-medows-is-the-first-ai-clinical-workspace): Most clinical AI solves one task. Medows is an AI clinical workspace built for the doctor on rounds — holds your list, answers grounded in the patient on screen, handover over WhatsApp.
- [Why handover defaults to WhatsApp, not email](https://www.medows.ai/blog/why-handover-defaults-to-whatsapp-not-email): We send handover over WhatsApp because the doctor on the receiving end already has it open. The whole story what it costs us, what we considered, and what would change our mind.
- [Why Doctors Need a Workspace of Their Own](https://www.medows.ai/blog/why-doctors-need-a-workspace-of-their-own): Five studies on how junior doctors actually spend their time, what handover failure costs in serious adverse events, and why the ward is the only part of modern healthcare still running on paper and memory.
- [Five Cases on the Ward: What an AI Workspace Looks Like in Real Use](https://www.medows.ai/blog/five-cases-on-the-ward-what-an-ai-workspace-looks-like-in-real-use): Hyperkalemia at 2 a.m., quiet sepsis on a Sunday morning, a drug interaction caught at order time, and a handover that didn't drop the pending lab - four composite cases from Indian wards showing how Medows actually works.
- [The Slow Goodbye: Why Paraquat Poisoning Kills Long After the Bottle Is Empty](https://www.medows.ai/blog/the-slow-goodbye-why-paraquat-poisoning-kills-long-after-the-bottle-is-empty): A weed-killer with no antidote, a patient who walks in talking, and a death that arrives weeks later as the lungs quietly turn to scar.
- [Why we built Medows as a workspace, not an EHR](https://www.medows.ai/blog/welcome): Most clinical AI products land in the EHR. We didn't. Here's why the doctor on rounds needs a workspace of their own, and what we learned building one alongside residents at AIIMS Bhubaneswar and RG Kar.
- [What "Ask Medows" Actually Means](https://www.medows.ai/blog/what-ask-medows-actually-means): Three things "Ask Medows" is — context retrieval, source-grounded generation, in-patient interface. Three things it explicitly is not.
- [The Eighteen-Minute Handover](https://www.medows.ai/blog/the-eighteen-minute-handover): Forty seconds per patient is enough for the urgent thing. Everything else gets dropped. What it means to design a handover that respects that math.
- [Why Doctors Don't Trust AI (Yet)](https://www.medows.ai/blog/why-doctors-do-not-trust-ai-yet): Three reasons doctors don't trust clinical AI yet, in order of how often I hear them. None of them are about the AI being smart enough.
- [The Casualty at 11 p.m.](https://www.medows.ai/blog/the-casualty-at-eleven-pm): Forty significant clinical decisions in an hour. Six hours of sleep. The pitch every AI clinical tool gets wrong.
- [The CCF Case Nobody Escalated](https://www.medows.ai/blog/the-ccf-case-nobody-escalated): A 62-year-old man in decompensated CCF by 10 p.m. The 6 p.m. obs were the inflection point. Nobody saw them as a slope.
- [What Changed When We Standardised Handover](https://www.medows.ai/blog/what-changed-when-we-standardised-handover): I-PASS cut preventable adverse events by 30%. The follow-up showed adherence to the bundle decayed by year-end. What that tells us about tool design.
- [The Burnout Number Indian Residency Does Not Talk About](https://www.medows.ai/blog/the-burnout-number-indian-residency-does-not-talk-about): 40-60% burnout in published Indian resident cohorts. The hours are the visible part. The cognitive-load-per-hour is the part we don't talk about.
- [Context-Aware AI vs. ChatGPT for Clinical Reasoning](https://www.medows.ai/blog/context-aware-ai-vs-chatgpt-for-clinical-reasoning): A junior doctor typing into ChatGPT on his phone gets a plausible answer. Why that answer is slightly useless for the patient three feet away.
- [The Morning Round in 90 Minutes](https://www.medows.ai/blog/the-morning-round-in-ninety-minutes): 90 minutes on paper. 1.8 minutes per patient in practice. What that actually means for the round you think you're doing.
- [Hyperthyroid Storm — The Case I Almost Missed](https://www.medows.ai/blog/hyperthyroid-storm-the-case-i-almost-missed): A 28-year-old with fever, tachycardia, and hypotension. Sepsis was the obvious differential. The TSH was the answer.
- [What AIIMS Taught Me About Residency Software](https://www.medows.ai/blog/what-aiims-taught-me-about-residency-software): Three things I didn't expect from a week shadowing a PGT at AIIMS Bhubaneswar. The paper list, WhatsApp, and the most stressful eight minutes of the day.
- [The DKA That Survived Because of One Note](https://www.medows.ai/blog/the-dka-that-survived-because-of-one-note): A 45-year-old man, DKA, an 11 p.m. ABG, and a handover line that meant the receiving doctor caught a worsening at 3 a.m. instead of 8.
- [The Stroke Time Window Under Heavy Load](https://www.medows.ai/blog/the-stroke-time-window-under-heavy-load): A 93-minute window. 140 minutes to needle. About 1.9 million neurons lost per minute. Where the time actually went.
- [What 5.9 Hours of EHR Actually Looks Like](https://www.medows.ai/blog/what-five-point-nine-hours-of-ehr-actually-looks-like): The Arndt 2017 EHR-event-log study, broken down by activity. Half an hour a day goes to navigation alone.
- [The Polypharmacy Trap in the Geriatric Ward](https://www.medows.ai/blog/the-polypharmacy-trap-in-the-geriatric-ward): An elderly man on warfarin, a new antibiotic, and the kind of interaction every pharmacy software catches — but only after the order is dispensed.
- [Pediatric Dosing in the Busy OPD](https://www.medows.ai/blog/pediatric-dosing-in-the-busy-opd): A 14 kg child, the wrong dose, and the dose-checking literature that says it's the system, not the resident.
- [Why We Still Hand Over on Paper](https://www.medows.ai/blog/why-we-still-hand-over-on-paper): The largest published reduction in preventable adverse events in residency literature came from a structured handover. Most of us still do it on a folded sheet.
- [The Twenty-Eight Patient List Problem](https://www.medows.ai/blog/the-twenty-eight-patient-list-problem): Miller's 1956 paper put working memory at 7 ± 2 items. The average Indian PGT carries 28 on their ward list. What that gap actually costs.
- [Sepsis That Walks In Talking](https://www.medows.ai/blog/sepsis-that-walks-in-talking): She walked into casualty post-op, day 2, with vitals that looked fine on every check. The slope was the diagnosis.
- [The Interrupted Shift](https://www.medows.ai/blog/the-interrupted-shift): A K+ of 5.9 that should have been caught at the bedside, the 9-minute interruption interval published in 2010, and why every ward tool we have assumes the doctor's working memory is intact.

## What Medows does
- **Ward list** — every patient on one card with vitals, complaints, active orders, and lab values, colored by acuity.
- **Ask Medows** — an AI consult that already sees the patient context (vitals, recent labs, completed tasks) and returns differentials and dosing with citations to clinical guidelines (e.g. AIIMS, ICMR).
- **Handover** — two lines per patient (Now / Pending) generated from shift context, sent to the next doctor over WhatsApp in one tap.
- **Vitals tracking** — quick capture between beds, trends over the last 6 hours per patient.

## Who Medows is for
- Junior doctors and residents (PGTs) in hospital wards
- Ward-based clinicians on admission days, night shifts, and high-volume rotations
- Solo practitioners covering multiple beds
- Doctors transitioning from paper handover lists to a digital workspace

## What Medows is not
- Not an electronic health record (EHR) and not a substitute for hospital documentation
- Not a multi-tenant hospital admin tool — no shared workspaces or admin dashboards
- Not a billing or scheduling product

## Pricing
Free for individual clinicians. There is no paid tier yet.

## Contact
- Founder enquiries (investors, hospitals, partnerships): alapan@medows.ai or alapanx@gmail.com
- Website: https://www.medows.ai
- LinkedIn: https://www.linkedin.com/company/medows-ai
- Reddit community: https://www.reddit.com/r/medowsai