MetaboliQ replaces the paper prescription pad with a dedicated clinical device. Offline-first. Zero behaviour change. Every prescription becomes a structured, patient-owned, FHIR-aligned health record — automatically.
Every interoperability initiative fails at the prescription moment because doctors won't slow down. The hardware has to be faster than paper — or it gets ignored.
Each consultation generates a prescription that disappears when the patient walks out. No structure. No searchability. The next doctor starts from zero.
Missing dose: 14–53%. Missing duration: 31%. Illegible to pharmacist: 3–11.5%. These are documented norms, not outliers.
India has 101M diabetics and 315M hypertensives requiring longitudinal medication tracking. Paper cannot provide it. Every follow-up begins from scratch.
The bottleneck is not technology. It is workflow.
India's 4–5Bn annual OPD prescriptions are handwritten. Patients leave with a paper slip. No structured data is created. No longitudinal record exists. The ABDM rails are built — but records still aren't flowing.
Every EMR or prescription app on the market requires doctors to change behaviour. They slow down the consult. They're heavier than paper. Adoption collapses at week 2. The bottleneck is workflow, not willingness.
iPads are too expensive and iOS-locked. Generic Android tablets aren't optimised for clinic environments. No device exists that is purpose-built for the Indian prescription workflow — offline-first, EMR stylus, ABDM-aligned.
MetaboliQ is a Device-as-a-Service company for Indian clinical infrastructure. We design, manufacture, and operate purpose-built clinical devices — starting with Glyph, the world's first dedicated smart prescription pad for Indian doctors.
Unlike software-only competitors, our hardware creates physical lock-in. A doctor who has our device on their desk doesn't switch — any more than a surgeon switches scalpel brands mid-procedure. The device is the habit. The habit is the moat.
Every prescription written on Glyph generates FHIR R4 structured data, feeds the patient's ABHA wallet, and trains our clinical AI — creating a compounding data asset that no competitor can replicate without years of prescription volume.
Every Glyph device is purpose-built for the Indian clinical prescription workflow — faster than paper, works offline always, outputs structured FHIR data automatically.
The doctor writes as usual. The system structures, signs, delivers, and stores — invisibly, in under 10 seconds.
Typed prescription with India brand-first autocomplete. Favourites, templates, "Repeat last Rx." Fully offline — no network dependency in the prescription flow.
Offline-firstNLP maps drug, dose, route, frequency, and duration to FHIR fields. Confidence scoring flags uncertain entries. High-risk medication alerts for doctor review.
FHIR R4 mappedSigned PDF generated on-device. WhatsApp link sent before the patient reaches the door. Doctor sees the timestamp: "8.3 seconds." Faster than handing over paper.
WhatsApp · SMS · PrintThe prescription becomes a wallet entry — a running medication timeline, current meds list, and emergency pack the patient controls and shares with consent.
Patient-controlledMedicationRequest structured to FHIR R4 and ABDM Implementation Guide. Immutable audit trail. Consent-gated sharing. DPDP-compliant from day one.
ABDM-alignedLab orders flow to connected labs. Diagnostic results return to the wallet. Pharmacy orders route automatically. Every connection multiplies the value of the record.
Labs · Pharma · InsurersEach component is irreplaceable. Together they constitute a novel technical system with no commercial equivalent in India or globally.
2,000+ Indian OPD brand names mapped to WHO INN generics. Specialty-ranked prescribing frequency. Trigram fuzzy matching. 15MB SQLite FTS5 local database. Sub-100ms autocomplete with zero network. Without it: reverts to generic-first vocabulary, product becomes slower than paper, abandoned in week one.
On-device MedicationRequest generation conformant with ABDM Implementation Guide. Zero server dependency in prescription creation flow. iText 7 PDF generation on-device in <300ms. Without it: becomes an unstructured PDF tool indistinguishable from existing Indian e-prescription platforms. Data layer ceases to exist.
Clinical NLP trained on Indian OPD patterns. Per-field confidence scoring. High-risk medication categories (anticoagulants, insulin, paediatric dosing) trigger verification before commit. Provenance labelling per field. Without it: clinical deployment is medico-legally indefensible. Medication errors create liability for prescribing doctors.
One prescription → signed PDF + patient wallet entry + FHIR R4 record. Invisibly. In under 10 seconds.
Offline-first. Prescription creation never touches the network. Local event-sourced SQLite store. Works in power cuts, basements, zero-signal environments. Zero prescription loss.
AI NLP extracts drug, dose, route, frequency, duration. Confidence scoring flags low-certainty fields. High-risk medication verification surfaced for doctor review. FHIR R4 MedicationRequest created in the background.
Patient wallet. Consent-gated sharing. ABDM HIE-CM integration. Lab results ingestion. Pharmacy orders. Insurer claims. Every connection raises switching cost for the entire ecosystem simultaneously.
The only metric that matters for adoption. Hyderabad pilot achieved speed parity at day 14. Day-4 parity is the active engineering milestone — drug vocabulary expansion to 8,000+ brand names in progress.
For chronic care patients, the previous prescription is the foundation. One tap pre-fills the entire prescription. Doctor reviews, adjusts doses, sends. Under 20 seconds total.
Pre-fills previous prescription. Edit doses, adjust durations. No retyping for follow-up patients.
T2DM review, HTN follow-up, URTI, paediatric fever. Common presentations in one tap.
Most-prescribed drugs surface first. Learned from the doctor's own prescription history.
Receptionist enters patient demographics. Doctor only writes the prescription. No admin overhead in the consult.
Prescriptions are written locally first. Sync happens in the background when connectivity returns. Zero prescriptions lost across 30 doctors, 30 days, including multiple connectivity interruption events in the Hyderabad pilot.
Event-sourced local store with hash-chained audit log. Every write is append-only. Conflict resolution handles device replacement and mid-sync disconnection. Patient safety is non-negotiable.
SQLite + Room ORM. All Rx written locally first. No UI blocking on network calls. Works in poor-connectivity clinics.
WorkManager handles sync when connectivity returns. Doctor never waits for network. Delivery happens silently.
Every prescription write, edit, and delivery is hash-chained. Medico-legal traceability built in.
Hyderabad pilot. 2 failures in 30 days — both resolved in <30 seconds via SMS fallback.
Patients receive their prescription on WhatsApp in under 10 seconds. It is simultaneously stored in their ABHA wallet — structured, searchable, shareable with any doctor with consent. The longitudinal medication timeline builds automatically.
Every structured product sits in the high-friction half. Every low-friction product produces no data. MetaboliQ is the only occupant of low friction + high structure.
| Tool | Speed vs paper | Works offline | Structured data | Solo GP fit | India brand vocab |
|---|---|---|---|---|---|
| Paper + WhatsApp photo | Fastest | Full | None | Perfect | N/A |
| Practo Ray | Slower (weeks 1–4) | Partial | Moderate | Weak | Generic-first |
| Eka Care | Moderate | Limited | Good | Moderate | Mixed |
| HealthPlix | Moderate | Limited | Good (specialty) | Poor | Specialist only |
| MetaboliQ | Faster by day 14 ↑ | Full — core arch ↑ | FHIR R4 ↑ | Primary ICP ↑ | Brand-first ↑ |
A doctor with our physical device on their desk doesn't switch. DaaS leasing means MetaboliQ owns the hardware layer indefinitely. No software-only competitor can replicate this without years of ODM relationships.
Doctor habit is the strongest moat in healthcare. Once "repeat last Rx" is muscle memory, switching means relearning 40+ patients per day. Churn cost is clinical, not financial — and clinical switching costs are total.
Every prescription enriches the dataset. Drug autocomplete improves. AI extraction sharpens. Safety signals calibrate for the Indian population. A larger dataset produces a better product — automatically.
After 12 months: medications, allergies, labs, referrals — all FHIR-mapped. No competitor can replicate this asset without replicating the years of structured capture that built it. The graph is irreplaceable.
Every lab, hospital, pharmacy, and insurer that connects raises the switching cost for every other party simultaneously. MetaboliQ becomes load-bearing infrastructure — not replaceable by a single competing app.
"Stripe didn't build a better payment form. It became the infrastructure. MetaboliQ doesn't build a better clinic management system."
Every prescription a doctor writes on MetaboliQ becomes a permanent, portable, patient-owned health record — automatically, without the doctor thinking about data infrastructure for a single second. The data creates itself.
Three phases. Each self-funding the next. Each building on the moat of the last.
Offline-first typed prescription. On-device PDF. WhatsApp delivery in <10s. India brand-first drug cache. Repeat last Rx. Favourite templates. Assistant mode. Hyderabad pilot → paid conversion.
Patient medication timeline and clinician viewer. Consent-based sharing with audit logs. Emergency pack QR. Handwriting mode beta. First lab integration — structured order flow, zero call-backs.
ABDM HIE-CM consent exchange. ABHA linking. AI medication reconciliation. Lab result ingestion. DICOM imaging. Full FHIR R4 + ABDM IG conformance. National health data infrastructure.
Onboarding 30 doctors in Hyderabad — GP, paediatrics, diabetology. White-glove setup. No IT overhead. If MetaboliQ isn't faster than paper by day 30, we refund everything.