Build your Agentic Hospital today.
Ask a question the way you'd ask your best manager. Your Chief of Staff sends the right agents into your hospital's own records, checks its answer before you see it, and gets the next step ready for you to approve.
- 9
- specialist agents
- 92%
- confidence bar
- 0
- changes without approval
Medikunj · Chief of Staff
Plans · delegates · verifies · acts on approval
Two short films
Watch the AI Chief of Staff work.
A hospital owner asks for today's collection, then for a plan to lift revenue 4%. The AI Chief of Staff reads the hospital's own records, rechecks an answer that scored below its 92% bar, finds four revenue leaks and builds the plan. Sample data.
›Transcript · Ask it anything
- Running a hospital, and still guessing your numbers?
- Just ask your AI Chief of Staff.
- It reads your own records, and answers.
- Now, ask the hard one.
- If it isn't sure, it doesn't guess. It rechecks.
- It finds the leaks, and builds your plan to plus four percent.
- Medikunj. Build your AI agentic hospital, today.
›Transcript · Tell it to do the work
- Every admission is a hundred handoffs.
- Now, just say it.
- Admin desk:Admit Rohan Verma to an ICU bed, book surgery with Dr. Arjun Mehta at 5 PM today, and inform the family.
- It admits, assigns the bed, books OT-1, and lines up the pre-op checks.
- The family gets a WhatsApp. The surgeon gets it on the phone.
- Surgery done? The bill updates itself.
- The TPA covers the package; only the exclusions go to the patient.
- At discharge, the RMO just asks.
- RMO:Draft Rohan's discharge summary.
- The summary writes itself.
- The doctor edits, approves, and nursing has it.
- Admission to discharge. One conversation.
- Medikunj. Run your entire hospital, agentically.
Want this running on your hospital's data?
What is an agentic hospital?
Software waits to be operated.
Agents get to work.
An agentic hospital is a hospital where AI agents handle the work between a question and a decision. They plan the task, read records across every department, check their own answer against the hospital's data, and stage the next action for a person to approve.
A normal HMIS stores what happened. When you want to know why collections dipped, someone has to find the report, export it, cross-check billing and bring you a guess. In an agentic hospital you state the outcome you want, and a Chief of Staff does the rest.
Medikunj AI Chief of Staff is the agentic layer of the Medikunj HMIS, the hospital management software built for nursing homes and hospitals in India.
Plan → Delegate → Verify → Act → Learn. On every question.
See the loop run on your own hospital's records.
The AI agents in your hospital
One Chief of Staff. A whole team behind it.
Every agent has a job and a boundary, and the boundary is enforced in code, not left to the prompt. Nobody reaches beyond their department.
Chief of Staff
plans · synthesises · evaluates · learns
Officers
Read-only: they can see, never change
Finance Officer
Collections, money in & out, delays and inconsistencies
Marketing Officer
Patient life cycle, follow-ups, growth, conversion
Operations Officer
Data gaps, front-desk pulse, your SOPs
Departments
Act only inside their own department
OPD Agent
Appointments, doctor-wise collections, AI prescriptions
IPD Agent
Census, admissions, services, discharges, final bills
Radiology Agent
Orders by modality, OPD vs IPD, reports
Pathology Agent
Lab orders, revenue, pending reports
Specialists
One patient, or the outside world
Patient Command Mode
Everything about one patient, and only that patient
Researcher
Outside benchmarks from public sources, each quote verified on the page
New agents plug into the same roster, and the Chief of Staff can reach them the day they're added.
Put this team to work in your hospital.
How it avoids wrong answers
If it isn't sure, it doesn't guess. It rechecks.
A separate evaluator scores every answer for coverage, grounding and consistency. Anything under 92% goes back with the critique, and the Chief of Staff comes up with a new plan and fresh working memory. When an answer relies on outside web sources the bar is 82%, and every outside figure must be quoted from its source.
Every figure is traced
Numbers in the answer must appear in what the agents actually read from your records.
A failed agent can't hide
If any agent errored or answered without reading data, confidence is capped far below the bar.
Counted by code, not the model
Lists of hundreds of patients are counted in code, with coverage shown, never estimated.
If it's still unsure, it says so
After three attempts it hands back its best answer, clearly marked below the bar.
Evaluator
Attempt 1 of 3
0%
Attempt 1
55%
Critique sent back to the planner
Attempt 2
65%
New strategy, still short
Attempt 3
98%
Every figure grounded
From a real test run of a single-patient question · read-only
Bring your hardest question to the demo.
Finding hospital revenue leaks
“Find the leaks and plan a 4% rise.” Answered with a plan.
Hard questions go to several agents at once. Each leak they find comes with the fix, and together they add up to a target you can hold your team to. The figures below are illustrative sample data, not a promised result.
Unallocated payments
Match receipts to open bills
Duplicate payments
Detect and void duplicates
Stale OPD bills
Daily pending-bill follow-up
Heavy discounts
Dual approval above 30%
Collections, next month
↗ +4%Projection from the Chief of Staff's plan · illustrative · sample data
Where is your hospital leaking money?
Who stays in control
It does the work. You make the call.
Nothing commits without you
Agents stage bookings, orders and bills. Only your Approve writes to the HMIS.
Boundaries in code
Officers are read-only. Departments act only inside their own department. Enforced by the runtime, not a prompt.
Patient data never becomes memory
Anything with a UHID, phone number or patient name is dropped before it's learnt.
Your SOPs, in your words
Rules and preferences come only from what you tell it. It never invents a policy.
Outside facts, quoted
Benchmarks are kept only if the exact sentence is found on the source page.
Every answer shows its work
Confidence, attempts, agents, tools and task memory, all one click away.
Runs on your hospital's own Medikunj HMIS data: OPD, IPD, billing, lab, radiology and pharmacy.
Autopilot for the work. You for the decisions.
FAQ
Agentic hospital: common questions
An agentic hospital is a hospital where AI agents handle the work between a question and a decision. They plan the task, read records across every department, check their own answer against the hospital's data, and stage the next action for a person to approve.
You ask it a question or give it an instruction in plain language. It decides which specialist agents to use (Finance, Marketing and Operations officers; OPD, IPD, Radiology and Pathology agents; Patient Command Mode; and a Researcher), runs them in parallel on your hospital's Medikunj HMIS records, combines their work into one answer, scores that answer, and stages any bookings, orders or bills for your approval.
No. Agents stage changes such as bookings, orders and bills. Nothing is written to the HMIS until an authorised person clicks Approve. The Finance, Marketing and Operations officers are read-only, and department agents can only act inside their own department.
A separate evaluator scores every answer for coverage, grounding and consistency. Figures must trace back to what the agents read from your records. Below 92% (82% when the answer relies on outside web sources), the Chief of Staff changes its approach and tries again, up to three times. If it is still unsure, it says so and marks the answer as below the bar.
Examples: "What did we collect today, and is anything off?" returns collections by payment mode and flags payments not allocated to a bill. "Find revenue leaks and plan a 4% rise next month" sends Finance, OPD and Operations agents to find leaks such as unallocated or duplicate payments, stale OPD bills and heavy discounts. "Which discharges in the last 3 months never came back to OPD?" counts every discharge in code and can stage follow-up visits. The figures shown on this page are sample data.
No. It remembers lessons, your SOPs and your stated preferences, but anything containing a UHID, phone number, record number or patient name is dropped before it is stored. SOPs and preferences are only taken from your own words.
Yes. The AI Chief of Staff works on the records in the Medikunj HMIS, which covers OPD, IPD, billing, laboratory, radiology and pharmacy for nursing homes and hospitals in India.
It is built for owners and administrators of nursing homes and multi-specialty hospitals in India. Book a demo to see it answer questions on sample data, and to discuss setting it up on your hospital's own records.
Still have a question? Ask it in the demo.
Build your Agentic Hospital today.
Your AI Chief of Staff, working on your hospital's own data. See it answer your own questions in a live demo.
Figures on this page are sample data unless marked otherwise.