AI-native Hospital Operating System
Ospia puts AI agents to work across admissions, billing, claims, pharmacy and inventory — working alongside your team, under your rules, on one record. You decide how much each one is allowed to do, and you can see exactly why it did it.
executive demonstration · 45 minutes · your numbers, not a canned demo
Illustration: Ospia's digital workforce. AI agents each carry a defined responsibility, a business impact, a schedule, and a named human they report to. Autonomy is a setting per task that the hospital configures.
§01 Why Ospia exists
The last generation of hospital software was designed to record what people did. The next one has to participate in it.
Beds, theatres, pharmacy, claims, staffing — every operational decision in a modern hospital is now mediated by a system. But those systems only store the outcome. The judgement, the coordination and the chasing stayed with people, and those people are the constraint.
An assistant bolted onto a menu is still a screen someone has to visit. Intelligence only changes a hospital's economics when it holds responsibilities — a defined scope, permissions, a schedule, and accountability for an outcome. That is a workforce, not a feature.
Their data models assume a human types every entry. Their architecture assumes capability lives in pages. You cannot retrofit an AI workforce onto a design that has no concept of an actor that isn't a person — which is why the assistants feel bolted on. They are.
Ospia was designed from the first line of code around AI-native operations: every capability a registered task any actor can invoke, every action an event kept permanently, every decision replayable, every rule configuration. The AI is not a layer on top. It is the reason the design looks the way it does.
We are not building a better system of record. We are building the layer a hospital actually runs on — so that adding intelligence, channels and capability over the next decade is configuration, not another hospital-wide migration.
§02 Why hospitals change their HMS
They do it because the one they have started charging them — in money, in time, and in the goodwill of the people who have to use it. These are the reasons we hear most.
A new discount rule or approval chain becomes a quotation, a release cycle, and a wait measured in weeks.
Timelines slip from months into years, and the value case quietly expires before go-live.
Software built for billing clerks gets handed to clinicians, who work around it — so the data is wrong where it matters most.
Lab here, pharmacy there, accounts somewhere else. Reconciliation becomes somebody's full-time job.
Staff carry four passwords and three mental models to finish one patient journey.
Every question leadership asks turns into a data request, a spreadsheet, and a week of waiting.
Your data is technically yours and practically hostage — leaving means starting over.
An assistant added to a design finished twenty years ago. It can answer questions; it cannot run anything.
Ospia was built so hospitals never have to replace their core platform again.
§03 What you actually buy
Not a feature list. The business case, with the mechanism named — so your team can check whether we can really do it.
Billing leakage, missed charges, stalled preauthorizations and aging invoices are watched continuously and escalated while they can still be recovered.
So what? Revenue gets protected during the month, instead of investigated after it.
The routine coordination work — chasing, checking, re-keying, reconciling — is handled by agents that never get tired and never forget a step.
So what? The same team runs more capacity without more headcount.
Admission, discharge, pharmacy and billing stop being serial paperwork. Patients get updates on WhatsApp instead of asking at a counter.
So what? Shorter stays, better reviews, more referrals from people who felt looked after.
Tooling with checksum verification, a parallel run reconciled every morning, and a per-hospital cutover with a rollback path that actually works.
So what? You are never one bad weekend away from a hospital that cannot bill.
Twenty-one digital employees with defined responsibilities, permissions and escalation rules — governed exactly the way you would govern a new hire.
So what? Night shifts, festival rushes and month-end stop depending on who happens to be on duty.
New capabilities install onto the platform rather than replacing it. New channels are thin surfaces over logic that already exists.
So what? No second migration in five years, and no second business case to defend.
§04 A day in your hospital
Nine ordinary operations, as they run in most hospitals today and as they run on Ospia.
TodayRegistration, insurance check, bed hunt and deposit handled at three counters, each waiting on the one before.
On OspiaOne task. Eligibility, bed allocation policy and deposit rules resolve together; the ward knows before the patient arrives.
TodayThe bill waits on the summary, the summary waits on the consultant, and the bed stays blocked all afternoon.
On OspiaCharges assemble continuously; the summary is drafted for sign-off. Discharge stops being a queue and becomes an approval.
TodayConsumables, procedures and services get delivered but never charged. Found at audit, if at all.
On OspiaEvery clinical event publishes a fact billing can hear. What was delivered and what was charged are reconciled as it happens.
TodayRejections arrive weeks later for reasons that were visible at submission. Rework is a department.
On OspiaDocumentation and coding gaps are flagged before submission; Insurance Watch chases what is stalled without being asked.
TodayLists overrun or run empty. Nobody sees the pattern until the monthly review.
On OspiaScheduling accounts for real case durations, and gaps are surfaced while they can still be filled.
TodayExpiry write-offs and stockouts discovered at the counter, by the patient standing at it.
On OspiaDispensing patterns drive replenishment; expiry and near-expiry stock surface early enough to be used.
TodayReorder levels set once, years ago, by someone who has since left.
On OspiaLevels learn from real consumption and supplier lead times, and adjust with the reasoning shown.
TodaySenior staff spend their week compiling numbers instead of acting on them.
On OspiaAsk in plain language, get a governed answer under your own permissions. Reports stop being requests.
TodayContext lives across tabs, and the doctor reassembles it from memory at every visit.
On OspiaOpening a patient assembles the relevant history, prior medications and comparable cases automatically.
§05 The AI workforce
Twenty-one digital employees. Each has a job description, permissions, a schedule, escalation rules, an audit trail and a named human it reports to — running on tasks whose autonomy level you set, and can change, at any time.
Chases invoices aged past the follow-up window, stops unbilled charges from ageing into write-offs, and reports clinical activity that produced no charge at all.
Reports to: CFO
Impact: lower days sales outstanding, less aged receivable value.
Chases preauthorizations that expired or aged while a patient is still admitted, drafts an appeal for every denial your own criteria say is appealable, and moves document-complete claims to the payer before they age.
Reports to: CFO
Impact: faster preauth turnaround, more denials overturned.
Moves purchase orders that have stalled in draft or in transit, and restocks consumables before the ward notices they're gone.
Reports to: CFO
Impact: shorter PO cycle time, higher supplier fill rate.
Notices stock falling toward its reorder level before it runs out, drafts the purchase order a storekeeper would have raised, and keeps reorder levels honest against what's actually consumed.
Reports to: COO
Impact: fewer stockouts, tighter days-of-cover.
Keeps expired stock out of the dispensary and gives the pharmacy enough warning to dispense short-dated batches first.
Reports to: Chief Pharmacist
Impact: lower expiry write-offs, higher FEFO compliance.
Watches bed pressure before it becomes an admission refusal, and flags wards running at or above the capacity-alert threshold.
Reports to: COO
Impact: steadier occupancy, fewer admission refusals.
Notices bookings at high risk of a no-show while a reminder can still change the answer, and keeps patient-submitted registrations from sitting unverified past the visit they were for.
Reports to: COO
Impact: lower no-show rate, faster pre-visit verification.
Walks every blocked discharge, hands each blocker to the colleague whose queue clears it, pursues the highest delay-risk patients first, and escalates anything nobody has cleared past the chase window.
Reports to: Chief Medical Officer
Impact: fewer blocked days per discharge, lower overstay rate.
Keeps discharge documentation signed and current, reviews stays that have run past expected discharge, chases departments holding up a ready discharge, and reconciles theatre cases left in a stale state.
Reports to: Chief Medical Officer
Impact: shorter length of stay, fewer unsigned summaries.
Makes sure every admitted patient is charted every shift, and fills roster gaps on wards that have patients in them.
Reports to: Chief Nursing Officer
Impact: no charting gaps, no ward left short-staffed.
Holds laboratory turnaround against the promised times, and keeps the four-eyes verification queue from ageing.
Reports to: Laboratory Director
Impact: fewer TAT breaches, no result stuck unverified.
Notices when laboratory turnaround drifts as a pattern rather than a single breach, and chases corrective actions past their due date.
Reports to: Chief Quality Officer
Impact: fewer overdue CAPAs, drift caught early.
Keeps unscreened or expired blood units out of the issuable pool, and triggers surveillance on prolonged critical-care stays.
Reports to: Infection Control Officer
Impact: lower HAI rate, no unscreened unit ever issued.
Keeps every practising clinician's registration current under NMC Reg 1.4.2, and escalates a lapsed registration before a prescription carries it.
Reports to: Chief Medical Officer
Impact: no lapsed credential ever reaches a prescription.
Checks that consent was recorded where the law requires it, ensures no AI-drafted clinical document is released unsigned, and chases what a consultation deferred once it comes due.
Reports to: Chief Compliance Officer
Impact: no consent gap, no unsigned AI draft, no dropped follow-up.
Keeps preventive maintenance and calibration from silently going overdue, and puts an overdue asset on the work-order board where somebody will see it.
Reports to: Head of Biomedical Engineering
Impact: higher PM compliance, less equipment downtime.
Clears leave requests that have sat undecided, and catches duty slots that clash with approved leave before the shift starts.
Reports to: CHRO
Impact: faster leave decisions, no roster conflicts on the day.
Notices integrations that have started failing, and gives a failing integration an owner instead of a retry counter.
Reports to: CIO
Impact: lower integration failure rate, tickets resolved inside SLA.
Notices when the platform's own automation keeps failing, and files a corrective action so a recurring fault has an owner and a due date.
Reports to: CIO
Impact: lower agent-run failure rate, fewer stuck proposals.
Holds the hospital's headline indicators against their thresholds, and projects capacity strain far enough ahead to act on it.
Reports to: CEO
Impact: capacity risk seen before it becomes a crisis.
Puts one honest picture of the hospital in front of leadership every day, and says plainly what is waiting on a human decision.
Reports to: CEO
Impact: decisions made on today's numbers, nothing left unrouted.
The badge on each card is how often the agent looks, not how much it is trusted to do. Autonomy is a separate setting, held per task rather than per agent — every change is an audited decision with a name attached. Nothing promotes itself, and nothing acts outside the permissions you granted it.
Interface preview. Ospia's clinical core is in build — see the phase plan for what is live today.
One console, whole workforce
Each agent reports what it handled, what it escalated and what is waiting on a human — with its autonomy level visible on every row. Nothing runs in the background that you cannot inspect, pause or roll back.
Open any row and you get the full reasoning: the recommendation, the evidence, the confidence, the alternatives considered and the policy it applied — the same envelope described in the explainability section below.
§06 What you inherit
A fair objection to any platform pitch: why should your hospital fund improvements that also reach everyone else? The honest answer is that the traffic runs towards you first — you start on what other hospitals have already proven, and you keep receiving it without paying again.
Bed allocation policies, approval matrices, claims checks, discharge criteria and segment pathways arrive already shaped by hospitals running them in production — not as a blank system waiting for you to discover the rules.
So what? A shorter implementation, because most of the thinking has already been done and tested.
When an agent gets better at catching a coding gap, or a workflow gains a safer default, it reaches you as an update. Not an upgrade project, not a change request, not a higher licence tier.
So what? The system you run in year three is materially better than the one you signed for, at the same price.
What can travel between hospitals is the shape of a configuration — a rule structure, a workflow pattern — never patient data, never your commercial terms, never anything identifiable. It is contractual, and it is opt-in.
So what? You take from the network without exposing anything to it.
The largest share of improvement is local: your case mix, your referral patterns, your tariffs, your consultants' preferences. The agents that get best at your hospital are the ones running inside it.
So what? The gains are yours first, and they start accruing from month one.
You go live on configuration shaped for your segment rather than a blank platform, so the implementation is shorter and the first month is calmer.
value: faster, lower-risk go-live
Agents adapt to your case mix and your rules. Everything you automate stays automated. Network improvements arrive as updates rather than projects.
value: leakage, rejections and delays falling
As your hospital's needs grow, the operating system identifies them and extends itself on the platform you already run. There is no scheduled rip-and-replace, and no second business case to defend to your board.
value: the migration you never have to fund
To meet the obvious objection directly: if this only paid back in five years it would be a bad purchase. It should pay for itself inside the first year — through billing leakage recovered, claim rejections avoided, and admission and discharge hours released. The compounding is not the business case. It is what stops the business case decaying afterwards, which is the part conventional hospital software has never offered.
§07 Total cost of ownership
The licence fee is rarely what a hospital system costs. The cost is in everything that has to happen around it — and that is where the two models separate.
Conventional model
Higher total cost of ownership
Spend rises with every year of use and every change you ask for.
The Ospia model
Lower total cost of ownership
Extend the platform continuously without another hospital-wide migration.
We will not put a percentage on this until we can show you one from a hospital that has lived it. What we will do is model it with your numbers — your volumes, your current licence and support spend, your customization history and your integration count — and let you decide whether the arithmetic holds. Ask for the TCO model on the demonstration call.
§08 Extensibility
Every module in Ospia ships as an installable package declaring its own routes, events, permissions and configuration. That mechanism already exists in the core — the marketplace is a storefront over it, not a new architecture.
Install capability packs onto a live tenant — specialty modules, compliance packs, reporting suites — with no code change to the core.
Phase 7Implementation and specialty partners trained and certified on the platform, with published competencies.
Programme formingNew agent capabilities composed from governed building blocks — bounded tools, prompt templates and evaluation sets.
Phase 7Proven operational workflows — discharge pathways, claims routines, procurement chains — installed as configuration.
Phase 7Specialty order sets, assessment forms, care pathways and documentation templates maintained by clinical authors.
Phase 7Independent developers build against published contracts and extension points, certified before listing.
Phase 7A connector catalog with configuration-driven onboarding: LIS, PACS, ERP, HRMS, payments, messaging, devices.
Core availableVersioned REST API with generated OpenAPI and a typed SDK, a published event catalog, and signed webhooks.
Core availableThe status on each card is deliberate. The mechanism is built; the storefront is Phase 7. We would rather tell you which of these you can use on day one than imply a marketplace exists before it does — see the phase plan for exactly where each one sits.
§09 Implementation
The single biggest risk in replacing a hospital system is not the software. It is the fortnight around cutover. This is the sequence we run, and the rollback path that sits under all of it.
Your current data, integrations, customizations and workflows are inventoried and scored for migration complexity.
Output: a complexity map and a realistic timeline
Configuration is drafted against your actual rules — numbering, tariffs, approval matrices, pathways — and signed off before build.
Output: an agreed configuration baseline
Historical data is moved with checksum verification at every stage, and reconciled against source counts and balances.
Output: a signed reconciliation report
Both systems process the same days. Differences are reconciled every morning until the delta is consistently zero.
Output: daily variance, trending to nil
Financial balances, clinical records and statutory reports are checked against the legacy system, line by line.
Output: sign-off from finance and clinical leads
Role-based training on the task bar rather than on screens — which is why it takes days rather than weeks.
Output: competency confirmed per role
Cutover runs to a written runbook with named owners, defined checkpoints and a rollback decision point at each one.
Output: a runbook executed, not improvised
On-site and on-call support at elevated intensity until agreed stability metrics hold for a defined period.
Output: exit criteria met before we stand down
Rollback is a first-class part of the plan, not an emergency measure. Until the parallel run is clean and your finance and clinical leads have signed, the legacy system stays live and authoritative. We do not cut anyone over on optimism, and we will say plainly when a hospital is not ready — including when that is inconvenient for us. See the full migration method →
§10 Industries
The platform is one. What differs is the configuration — pathways, rules, roles and reporting — set up for your segment rather than adapted by you after purchase.
Cross-department flows, shared theatres and diagnostics, consolidated reporting across service lines.
Deep pathways for one discipline, with packages and outcome tracking built around them.
Teaching workflows, resident supervision, academic records and statutory reporting alongside care.
Scheme eligibility, public-health reporting and high-volume outpatient flow with minimal training overhead.
High-throughput clinics, optical retail and per-eye procedure records handled as first-class concepts.
Protocol-driven regimens, cycle scheduling, day-care chemotherapy and long-horizon follow-up.
Cycle tracking, embryology records, consent-heavy pathways and outcome reporting across attempts.
Antenatal through delivery and paediatric care on one continuous record for two linked patients.
Tooth-level charting, treatment plans staged over visits, and package-based billing.
Multi-centre sample logistics, analyser integration, turnaround tracking and referrer relationships.
Segment-specific configuration packs install onto the same platform — no separate product, no forked codebase, no version of Ospia that only your hospital runs. Ask us for the detailed brief for your segment and we will walk you through the configuration as it would ship for you.
§11 The platform underneath
Everything on this page so far is a claim about outcomes. This section is the mechanism — the part your IT team and your architects will want to interrogate. It is here to be checked, not skimmed.
Numbering, bed allocation, pricing, discounts, approval matrices, referral and consent rules, clinical pathways and discharge criteria are versioned configuration evaluated by one engine.
Every action is an event and every event is kept permanently. Any AI recommendation can be reconstructed months later with its exact model, inputs and reasoning.
Every capability is a registered task. A screen, the command bar, voice, an AI agent and a partner's API are all just different ways to invoke the same one.
Illustration: Ospia's task bar resolving a plain-English instruction into a registered task with typed parameters, a required permission, an autonomy level and the events it publishes.
"Generate today's discharge bills" resolves to a task invocation, not a path through a menu. That is why training is short, adoption is high, and a new surface is weeks rather than a project.
An AI agent is not given a browser and a login. It gets a permission-scoped subset of the same task registry, under the same authorization, producing the same audited events. There is no back door because there is no second door.
Undo on user actions, rollback and compensation on workflows, version history on records, replay on AI decisions. A system people trust is one where an error is a Tuesday, not a catastrophe.
§12 The autonomy ladder
Every task is built capable of full autonomy and ships set to whatever level you are comfortable with. This is the control most boards ask about first — so it is a setting, not a promise.
Risk classifies the action; maturity configures how far automation may currently go for that action, at your hospital. A low-risk task may sit at L4 on day one; a high-risk one may sit at L1 for two years and then move — because you moved it, on evidence, with a signature attached.
§13 Explainable AI
Not a policy commitment — a response contract. Nothing reaches a clinician or an administrator without answering these questions, and nothing that ever happened stops being reconstructable.
Recommendation
Raise the reorder level for Amoxicillin 500 mg from 400 to 620 units.
Why?
Consumption over 60 days is up 34%; at the current threshold cover falls to 11 days before the next delivery window.
Evidence
1,842 dispensing events · 3 supplier lead-time records (mean 6.2 days) · 2 stockouts last quarter.
Confidence
0.86 — lead-time variance is the dominant source of uncertainty.
Alternatives considered
Hold at 400 and shorten the delivery cycle · raise to 520 with a weekly review.
Policy references
Rules engine — inventory.reorder.service-level = 0.98, formulary class B.
Expected outcome
Stockout probability falls from 0.19 to 0.02; holding cost rises ~₹9,400 a quarter.
Model, model version, prompt version, exact inputs, output, who approved it and what executed. Complete enough to run the decision again and get the same answer — which is what auditors, insurers and courts actually ask for.
All model access goes through one router with routing policy per task class — cost, latency, language, data sensitivity, residency. Switching provider, or keeping sensitive classes on a private model, is configuration.
Model registry, versioned prompts, evaluation sets and performance monitoring behind every agent — with identity, permissions, KPIs and escalation rules in front of it.
§14 Architecture
One deployment, one codebase, one database per hospital — divided internally into fully isolated domains, each owning its own data. This is the part that keeps the promises above true in year five.
A module may import itself, the contracts package, and the kernel. Anything else fails the build.
A repository referencing a table outside its own schema fails the build. No allow-list, no exceptions.
Domain logic may not import infrastructure, presentation, or any I/O library. Purity is checked, not requested.
The kernel may not depend on any module or contract. A "utility" naming a domain noun belongs in that domain.
Contracts carry no runtime dependencies; breaking changes to types or event schemas are caught on every pull request.
A module ships with its tasks, permissions, events, AI tools, flags and seven documents registered — or it does not ship.
Alongside these run the ordinary ones — strict types, both-ways migrations, coverage floors, contract tests, an authorization matrix, accessibility scans, performance budgets, dependency and secret scanning. The ladder only ever grows. Architecture written in a document decays; architecture written in a pipeline holds.
§15 One record, whole hospital
The full clinical, financial and operational catalog on a single patient record — plus the platform capabilities a conventional system has nowhere to put.
§16 How Ospia compares
Written to help you evaluate, not to attack anyone. Every category below contains good products — the question is which set of trade-offs you want to live with for the next decade.
If you are comparing us against a specific vendor, ask us — we will give you an honest, sourced assessment, including where the other product is genuinely stronger. Any vendor who tells you they win on every line is selling, not helping you evaluate.
§17 Trust & compliance
Ospia is early. Rather than dress that up with borrowed logos and rounded-up numbers, here is the honest position — and everything we can already demonstrate on a call.
One physical database per hospital, row-level security, field-level encryption on personal data, and a hash-chained audit log that fails verification if anyone edits history.
Self-hosted or managed cloud, your choice. Everything exportable, an open FHIR R4 API, and the full event history belongs to you. Leaving should be as open as arriving.
Workflows are reviewed with the doctors, nurses and administrators who have to live in them. We are expanding our clinical advisory panel — if you would like a seat on it, tell us.
We are onboarding a small number of design-partner hospitals rather than publishing customer counts we have not earned. Ask us exactly what is live and we will show you the phase plan below.
Design-partner hospitals appear here as each one goes live and agrees to be named.
Each published with the hospital's permission, the methodology stated, and the numbers they measured themselves.
Target commitments, contracted per agreement. Measured attainment will be published here once we have a service history worth publishing.
When we have hospitals live, their names and their numbers will appear here — with their permission and with the methodology stated. Until then this section stays honest, because a platform that asks you to trust its audit trail cannot start by overstating its own record.
§18 Resources
We would rather you arrive at your own numbers than accept ours. The leakage calculator below is live now — no email, no form, nothing gated. The rest are in build; ask and we will run any of them with you directly in the meantime.
Your beds, occupancy and rejection rate against the two leaks that account for most of it: charges never billed, and rejections never recovered. Every assumption is visible and yours to change.
Open the calculator →Model the recovery from reduced billing leakage, fewer claim rejections and shorter length of stay against your actual volumes.
Request it run for your hospital →Where your data, processes and governance stand today, and which agents would be safe to run first.
Request an assessment →An honest benchmark of your current systems against where comparable hospitals are heading.
Request a benchmark →What has to be true — data, people, process — before a cutover is safe to schedule.
Request a readiness review →Scope the move from your current system: data volumes, integrations, custom rules and realistic timeline.
Request a scoping call →A session for your IT leadership and architects: the platform, the gates, the security model, and your hardest questions.
Book a deep-dive →Ask three questions and the difference resolves itself. One: can you replay a decision the AI made four months ago — the exact model, prompt version, inputs and output? Two: can you set how far automation goes for one specific task, and show the audit record of who changed it? Three: can you switch AI provider without a project? Most systems answer no, no and no — because the AI was added to an architecture that had already been decided.
Act outside the task registry, or act above the autonomy level you configured. Agents invoke the same permission-checked tasks your staff do, under the same authorization, producing the same audited events. Above L2, execution requires a named human. At L4, it requires a policy you approved — and every run still lands in the decision ledger, replayable.
The hospital keeps running. Ospia is a complete system with no external AI configured at all; deterministic fallbacks cover the assistive paths. AI adds speed and foresight; it is never a dependency. And because no provider is named anywhere outside the model router, switching providers — or routing sensitive task classes to a private model — is configuration.
The target is that 90% of what a hospital asks for is configuration, not code — and it is measured rather than asserted: every change request gets classified config-or-code, and a code answer is treated as a design failure worth examining. Numbering, allocation policies, pricing, approval matrices, pathways, consent rules and discharge criteria are versioned data evaluated by one engine, not conditionals in a fork maintained just for you.
Yes, through a connector catalog rather than a project: FHIR R4 and HL7v2, DICOM/PACS, LIS/RIS, ERP and accounting, HRMS, government portals, payment gateways, WhatsApp/SMS/email, and device feeds. Each connector declares its own configuration schema, so onboarding one is a configuration exercise. Outbound, every domain event can be subscribed to as a signed webhook.
As an engineering programme, not your problem to solve: migration tooling with checksum verification, then a parallel run where both systems process the same days and get reconciled every morning, then a per-hospital cutover with a rollback path. We do not cut anyone over on optimism, and we will tell you plainly when your hospital is ready rather than when our quarter needs it.
You do, in the plainest sense. Each hospital runs on its own physical database — self-hosted if you prefer. Everything is exportable, the FHIR R4 API is open to you, and the permanent event log is yours as much as the tables are. Leaving should be as open as arriving, or the promise is not worth much.
§19 Company
Ospia is built under a written engineering charter in numbered, gated phases. Nothing merges without passing the full gate ladder. Here is the sequence, what is done, and what is next.
Ask us where any capability on this page sits — the answer is a phase number, not a shrug. We would rather show you the sequence than imply everything already exists.
§20 Built for India
Indian regulation is not a localization layer here. It is configuration and rules the platform enforces at the moment of writing — and that the agents watch continuously.
Registration is ABHA-ready and every use of personal data traces to recorded consent — consulted before use, not attested after the fact.
Generic-name prescribing, prescriber statutory identity on every document, serialized certificates, and the 72-hour record-release clock escalated before it lapses.
HSN/SAC per line, CGST/SGST versus IGST by place of supply, e-invoice payloads with deterministic IRN, and a TDS/TCS ledger.
Peer-to-peer video — media never touches the server. Consent gated before the call, Schedule-X drugs hard-blocked in-call.
CAPA, live risk register, HAI surveillance and antimicrobial stewardship — the trail assessors ask for, produced by daily work rather than a pre-audit scramble.
Ten Indian languages, WhatsApp and SMS notices, a PII-free token board, voice-first booking, and prescriptions explained in plain language.
§21 Our mission
Healthcare runs on people doing careful work under pressure. Software should absorb the pressure, not add to it.
Hospital software was built when digitizing the paper record was the ambition, and it achieved that. But a system that only records cannot help with the thing hospitals are actually short of — capacity, attention, and time. Meeting the next decade needs a different starting assumption.
We are unwilling to put AI into clinical and financial operations on the basis of trust alone. So the platform was designed the harder way: every decision replayable, every autonomy level configured by the hospital, every action produced through the same permission-checked path a person would use. Governance first, capability second — because the reverse does not survive contact with a real hospital.
We publish our engineering charter, our phase plan and our architectural gates because a hospital is making a fifteen-year decision. You should be able to check whether we are building something durable, hold us to the sequence, and see plainly what is finished and what is not. That is also why this site tells you where we are rather than where we would like you to think we are.
§22 Explore in depth
This page is the argument in summary. Each of these goes into the detail your team will want before a decision.
The capability model, the task registry, the rules engine and how it all fits together.
Modular monolith, isolated domains, the event backbone and the CI-enforced gates.
All twenty-one digital employees, the autonomy ladder and the governance model.
Tenant isolation, encryption, access control, audit chain and the security programme.
ABDM, DPDP, NMC, NABH, GST and the standards we support today.
Packages, partners, AI skills, workflow packs and how extensions are certified.
How a hospital goes live: phases, roles, timelines and what we need from you.
Data migration, parallel running, verification, cutover and rollback in detail.
API, SDK, event catalog, webhooks and extension points.
Implementation, technology and academic partnership programmes.
Where we are today, what we can prove, and our support commitments.
Configuration for your segment — ten of them, each with its own workflows.
Whitepapers, architecture papers, guides, documentation and the video library.
Our mission, the engineering charter, the phase plan and how to reach us.
How to evaluate Ospia against the systems you are also considering.
The category argument in depth: why hospitals should stop buying HMS, and how to judge AI claims.
A 45-minute executive demonstration on your numbers.
§23 Next step
We seed a hospital with synthetic data shaped like yours, put the digital workforce on duty, and let your team ask it the questions they ask their MIS today. Bring your hardest month-end.
synthetic data · zero real patients
self-hosted or managed cloud
one database per hospital