CubixCode Technologies · An invitation to partner
The trusted record between
Bharat's doctors and labs
A working product, a clear business, and a wide-open window — right as the government hands the whole sector a tailwind. We're looking for doctor- and lab-partners to build and grow the network with us.
Prepared by CubixCode · for prospective doctor & lab partners
A disconnected market: doctors can't see the data, labs can't reach the doctors
The doctor's side
- A patient's reports pile up across many labs over years — arriving as PDFs, scans & photos, every lab a different layout.
- At the desk the doctor flips paper: no trends, no longitudinal view → repeat tests, missed patterns.
The lab's side
- Small & off-grid labs are starved of referrals and have no digital link to the doctors who send them work.
- Results go out on paper / WhatsApp; big labs' APIs are gated B2B, and ABDM interop is patchy — the long tail has none.
The moat is not OCR — and no longer the EMR
OCR is commoditising (LLMs / cloud OCR). The durable value is normalised + longitudinal + trusted + point-of-care data, aggregated across fragmented sources.
Multi-channel ingestion
Lab API where it exists → ABDM/ABHA where connected → PDF/OCR as the always-works fallback. OCR is just one channel.
Normalisation is the hard part
Units, reference ranges, test names & codes vary per lab. Cross-lab normalisation is the real moat (and the real grind).
Trust is the asset
Source links, verification status & plausibility flags — provenance is the currency that earns the doctor's confidence.
The govt validated the category — and commoditised the EMR
On 29 June 2026 the Centre launched e-Sushrut Clinic (built by C-DAC): a cloud clinic system for small clinics & PHCs — ₹299–499/month, first 3 months free, ABDM-native, ~800 facilities live on day one.
Category validated, awareness funded
The government is now evangelising cloud clinic software to exactly our users — driving ABHA adoption and digitisation at its own expense. We ride that wave.
The EMR is now a utility
A subsidised ₹299 product puts a price floor under basic EMR. Competing as "another cloud EMR" is a race to zero against the government. So we don't.
Sit above it, on the same rails
e-Sushrut has no doctor–lab network and no research pipeline. We interoperate via ABDM and become the value layer — addressable even to clinics already on e-Sushrut.
A huge market — and the timing window is open
doctors in Bharat
Registered allopathic doctors — most in small private clinics, exactly our long-tail wedge.
digital-health growth
Bharat's digital-health market is ~$15B today → ~$100B by 2033 — software the fastest-growing slice.
ABHA-linked records
Doubled in 15 months; 90 cr national health IDs created — the rails are already here.
A neutral network: doctors get the software, labs pay for demand
- The doctor is distribution, not the payer — software is free/cheap so it spreads. Every clinic that adopts generates lab orders.
- Labs are the payer — small & off-grid labs pay for the one thing they lack: digital reach to referring doctors. A payer the ₹299 government EMR never touches.
- We are neutral — unlike Tata 1mg / Practo, we don't own a lab or pharmacy, so we never compete with the labs on our own network. That neutrality is the moat.
- The compounding prize: the consented, de-identified longitudinal record we accumulate — research-grade data no one else holds.
The two-sided network
Patients bring the data & the consent; choose their lab.
Doctors get cheap software → prescribe tests. Our reach.
Labs pay to receive referrals + feed results back. Our payer.
Colleges & pharma license de-identified research data. Our upside.
Labs fund the network · data compounds the value
Labs pay for reach
A connected-lab subscription + a small per-result technology fee for every report routed & delivered through the network. Labs pay for demand, not software.
Doctor software: free / near-free
Flat, low, independent of referral volume (see the legal note). It's customer-acquisition — the more doctors, the more lab orders, the more labs pay.
Research-data licensing
De-identified, longitudinal datasets to colleges, pharma & CROs. High-margin, defensible — a second revenue leg once the data exists.
Money flows lab → platform, never lab → doctor
Bharat.s law (MCI/NMC code) bars any cut, rebate or referral fee to the doctor ("cut practice"). So: the doctor's price is flat, the lab pays the platform, and the patient picks the lab from connected options — the doctor prescribes the test, not the lab.
Premium tier · On-prem
Self-hosted / larger-clinic licences for the privacy-first minority. Not the volume play — a margin add-on on top of the network.
Pharma is already asking — the network mints research-grade data
Every verified, ABHA-linked report — tied to diagnosis, medication & outcome from the clinic side — is real-world data. Used well, the network is a data refinery: scarce, Bharat-specific, longitudinal, provenance-checked. This isn't a someday prize — it's exactly what pharma buys today.
RWD → RWE
De-identified RWE for safety, label expansion, market access & comparative effectiveness — increasingly accepted by regulators (CDSCO / FDA / EMA). Sold as datasets & analytics.
Disease registries
Condition cohorts (diabetes, CKD, oncology…) with structured longitudinal follow-up. Sponsors pay us to stand them up on the network — recurring & defensible.
Trial enablement
Patient/site identification, recruitment, decentralised capture & external / synthetic control arms from our RWD. Picks-and-shovels — never a CRO (CDSCO-regulated).
Why our data is credible
Verification-at-source (auditable quality) · ABHA linkage (longitudinal, cross-provider — what most of Bharat.s RWD lacks) · clinical context from the CMS turns lab numbers into evidence. Labs are the spine; context compounds it.
Who pays for it
Pharma (RWE / HEOR / market access) · academic & clinical research · public-health & epidemiology · insurers · diagnostics-AI training. Bharat.s real-world data is scarce → distinctly valuable.
The government pays clinics, labs and us to go digital
Bharat's ABDM runs a Digital Health Incentive Scheme: cash for every lab report digitised and linked to a patient's national health ID (ABHA). It pays every side of the network:
₹10 / report
A subsidy that pays the clinic to adopt digital records — i.e. to adopt us. The tool helps pay for itself.
₹15 / txn
Diagnostic labs earn per ABHA-linked report (above 500/mo, KYC-verified). The govt subsidises the exact data labs feed our network.
₹5 / report
As the DSC / LMIS behind the record — on top of lab fees, scaling with volume.
Designed for it — deliberately not yet
- Full compliance is a real program: ABDM v3 APIs, a security cert (WASA), DSC registration.
- The economics only clear at scale — break-even is hundreds of GP clinics, or ~35 diagnostic centres.
- Earning it means records enter the national exchange — consent + compliance work we must get right before we switch it on.
- FHIR-native model · ABHA-optional from day one · the read-API seam → a build-later, not a rebuild.
- Cloud-default makes ABDM linkage natural; the on-prem tier claims the same incentive via an opt-in, consent-gated bridge.
- When: once ABDM compliance is table-stakes, or reach makes ₹5×volume material — starting with diagnostic centres.
Worth it at what scale? Run the numbers
DHIS pays us ₹5/diagnostic report linked to a KYC-verified ABHA, above a 100/month baseline per clinic — only if we carry the compliance machine. Drag the dials; every figure is rough & editable.
A contested space — but the neutral doctor–lab network is open
| Category & players | Their strength | The gap we exploit |
|---|---|---|
| AI health records / report parsing Eka Care closest | ABHA + AI report parsing; consumer & doctor reach. | Cloud-first, broad consumer play — not on-prem / trust-first for the long tail. We go deep on point-of-care multi-lab trends + local trust. |
| Clinic EMR / management Practo · HealthPlix · DocOn (Reliance) | Full clinic management, scale, brand. | Heavy & cloud; aim at larger practices. Weak on multi-lab longitudinal report aggregation + verification. |
| Consumer lab aggregators 1mg · PharmEasy · Healthians · Redcliffe | Booking + in-app report storage; consumer scale. | Consumer-facing and they own their own labs/pharmacy → they compete with the local lab. We're neutral — we connect independent doctors & labs, taking no side. |
| Govt cloud EMR e-Sushrut Clinic · C-DAC new | Subsidised (₹299/mo), ABDM-native, government reach & awareness. | Basic EMR only — no doctor–lab network, no research pipeline. It commoditises the EMR and drives ABHA adoption → we sit above it on the same rails. |
| The national rail ABDM / ABHA | Government interoperability standard & consent rails. | A rail, not a product; adoption patchy → ride it, don't fight it (FHIR-aligned by design). |
The neutral doctor–lab network
We connect independent doctors & independent labs and hold the trusted longitudinal record between them — neutral by design, with PDF/OCR as the universal fallback where no API or ABDM reaches.
Could the EMR layer absorb us?
Govt/funded EMRs own the desk — but not the two-sided network or the data asset. Our moat: neutrality + the accumulated verified record + geographic network density.
Every lab, every year — one screen at the deskrunning today
Not a mockup. This is the working product on the clinic's own computer: a patient's whole lab history, pulled from reports across different labs and years into one trended view.
One patient, every lab, years
Reports from any lab land in a single timeline — no flipping paper, no re-typing.
Normal band shaded in
Each value is plotted against its reference range, so a drift out of range jumps out at a glance.
Change since last visit
Latest reading and the delta vs the previous one, on every parameter card.
Built in two clean halves — cloud‑first, with an on‑prem tier
Two clean halves
One half turns documents into clean data; the other shows it to the doctor. They talk through a standard health-data format (FHIR), so each can improve on its own.
Cloud-first, so the network can exist
Cross-doctor history, lab-fed results and pooled research only work with a shared cloud node. Bharat-hosted, encrypted, consent-gated — the market (and the government) already accept cloud.
Self-host for the privacy-anxious
The on-prem build we already have lives on as a paid premium tier for larger or privacy-first clinics. Privacy becomes an up-sell, not a constraint.
Two products, one contract — cloud or on-prem
🖱 Click any block — a product, the API seam in the middle, or the installer frame — for its role, why it matters, and the critical points.
Centralise extraction · localise verification
- Verification = transcription fidelity ("does it match the source?") — clerical, done by existing clinic staff in spare minutes.
- Confidence-tiered: clean & plausible auto-passes; only flagged/low-confidence gets a full check. The cost lever and a pricing lever.
- Clinical validation stays with the doctor — passively, at the point of care.
Doctor as steady-state verifier
Kills the "free the desk" value & the status problem. Bootstrap only — recruit believer design-partner doctors to seed trust.
The trust machinery
Source-page deep-links · verified/unverified flags · plausibility flags · page-anchored verify screen.
The trust flow end to end — flag → track → confirm against the source. Click any screen to enlarge.
Match the bar on security — then lead on privacy
Doctors trust certified data-handlers. Peers set the bar at ISO 27001 + HIPAA. We match it — then go further on privacy, the one thing our whole product is built around. A sequenced roadmap, not a wall of logos.
The security floor
ISO 27001 · HIPAA · DPDP Act compliance. The recognised baseline — what the market already expects.
Certify what we claim
ISO 27701 (privacy management). Privacy-first is our brand — so we certify it, not just say it. Pairs naturally with DPDP.
Interoperability & cloud
ABDM Milestone + WASA · SOC 2. Sequenced to the ABDM and hosting steps — earned when they're needed, not before.
Built with clinicians · validated by a medical college
In healthcare, trust is the gate — and the fastest way through it is to borrow an institution's. A research partner whose name a wary doctor already respects does more than any feature list.
A medical college
"Research partner: XYZ Medical College" earns instant trust, gives us an ethics committee for the data play, and feeds the student flywheel.
A teaching hospital
A real-world testbed + clinical design input — so "built with clinicians" is a claim we can then make truthfully.
Keep it neutral & honest
Prefer non-competing colleges over corporate chains (protects our neutrality); structure as an MoU, not equity; market a name only once signed; say "research partner", never imply a clinical/device endorsement.
Two speeds: labs & MRs fund now, colleges compound later
Labs · MRs · pharma reps
MRs visit clinics daily and own the doctor relationship. Small & off-grid labs onboard fastest — they have nothing to migrate.
Saturate one geography
Two-sided networks die spread thin. Densely wire the doctors + labs of one city → referrals actually flow, support is feasible, and it becomes the reference case.
Colleges & fresh doctors
Free student access + research datasets → citations + habituation → they open clinics as customers. Low CAC, compounding, funded by the network.
Stand up the network; the data follows
✓ Built & working
- Patient records & side-by-side compare
- Auto-read values & plot trends
- Out-of-range safety-net + auto-track
- Staff verify-against-source screen
- Full clinic system (visits · Rx · billing · pharmacy)
- Two-product split over a standard (FHIR) data layer
- On-prem build — now the premium tier
◆ Now — stand up the network
- Cloud hosting (Bharat, encrypted, consent-gated)
- Doctor→lab referral + result feed
- ABDM / ABHA interop
→ Next
- Patient lab-picker (choice of connected labs)
- Lab middleware for labs already on a system
- Read scans & photos (OCR) · more labs
↗ Later
- Research-data licensing + college program
- DHIS incentive machine at scale
- Patient app
The sequence
Saturate one region's doctors + labs → make referrals flow → light up the data asset → colleges & DHIS at scale. Depth in one geography before breadth.
Do the numbers
Lab willingness-to-pay × referrals/clinic × onboarding cost × churn → does the lab-funded model clear at regional density?
We've built the product. We want doctors and labs to build the network with us.
What a doctor brings
Clinical credibility peers trust · real-desk product input · and the cheapest channel there is — doctor-to-doctor referral across your region.
What a lab brings
The other side of the network — become a connected lab, feed results digitally, and get referrals from every doctor we sign in your area.
The build muscle
A working product, the engineering, the data architecture & the strategy — already running. Plus a founding-partner stake (equity and/or revenue-share) for early believers.
Connect the doctor and the lab.
Own the record — and the data — between them.
A working product, a clear path, and a government tailwind that just opened the window. Come build Bharat's neutral doctor–lab network with us.
Let's talk · CubixCode Technologies · [ your email · phone ]