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Ask a car mechanic why the rocket couldn't fire its afterburn near Mars. He's brilliant at his job. He just isn't a rocket scientist.

That's what you're doing every time you ask ChatGPT or Claude about your business. Meet Tojo — three layers, one Decision Engine, built to think like a CEO in your industry.

Tojo
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01

Ask questions a CEO asks another CEO. Not someone who only summarises books.

Every layer of Virevo is built the same way — real operating judgment, not encyclopedic recall.

02

Information isn’t wisdom. An encyclopedia isn’t experience, strategy, or trust.

Every layer of Virevo is built the same way — real operating judgment, not encyclopedic recall.

03

You know more about your business than any AI. Tojo knows what to do with it.

Every layer of Virevo is built the same way — real operating judgment, not encyclopedic recall.

.01 — Three Layers

Executive Decision Optimization, applied in three layers.

Two layers help you decide. The third makes sure the decision actually happens — across every department, every day. Keep scrolling — each layer gets its own moment.

  • 01 Decision Engine Chat Agent
  • 02 Business Mapping & Simulation
  • 03 Decision Implementation & Automation

01 — Decision Layer

Decision Engine Chat Agent

Talk to Tojo the way you’d talk to a CEO who has already run a business like yours — one that knows your margins, your seasonality and your constraints before you explain them.

02 — Strategy Layer

Business Mapping & Decision Simulation

Every tangible and intangible variable in your business, mapped into one living model you can test against before you commit a rupee or a rota.

03 — Execution Layer

Decision Implementation & Automated Operations

Custom automation for healthcare and hospitality, built to run every department the way you would — and to keep running it at 3am.

.02 — Decision Layer

Talk to another CEO. Not someone who’s just read everything.

A general LLM has read every business book ever written. It has never sat in your boardroom. Ask another CEO who has actually solved your exact problem, and you get judgment — the specific fix, sized for a business exactly like yours.

Try it — pick a question Tojo has already been asked:

  • Should I open a 40-bed wing or invest in ICU?
  • Why is my OT utilisation dropping?
  • How do I cut discharge time without hurting care?

Standard LLM Assistant

AiStandard LLM Assistant

Should I open a 40-bed extension wing, or put that capital into ICU capacity instead?

“Expanding capacity is a significant decision. Consider market demand studies, capex requirements, expected ROI timelines, staffing costs, and regulatory approvals before proceeding.”

Generic. Encyclopedic. Not yours.

This is what any general AI gives you.

Same question, answered by Tojo

TTojo Live
Tojo

Same question, two answers

A guided tour: one CEO question, a generic AI on its top model, then Tojo.
Generic AI top model, general knowledge
The CEO asks

No. You should accept that insurance approvals are sometimes outside the hospital’s control. You should not accept that the resulting discharge delays are an unavoidable cost of running a hospital.

For a 345-bed super-specialty hospital in Kolkata, this is not merely an administrative inconvenience. It is an operational bottleneck that can affect revenue, bed availability, patient experience, nursing workload, and even the utilisation of critical-care capacity.

And given that you’ve already tried multiple interventions, I would change the question. Rather than asking, “How do we make insurers approve faster?”, ask:

“How do we run the hospital so that an insurer’s delay causes the least possible disruption?”

That is a very different problem — and one the hospital has substantially more control over.

1. First, challenge the assumption that nothing can be done

There is an important regulatory point here. Under the IRDAI Master Circular on Health Insurance Business dated 29 May 2024, insurers are required to grant final cashless discharge authorisation within three hours of receiving the hospital’s discharge authorisation request. If the delay beyond three hours results in additional charges, the circular provides that those charges are to be borne by the insurer from its shareholders’ funds.

That gives you a concrete basis for escalation. But the clock starts when the insurer receives the formal discharge authorisation request — not necessarily when the doctor advises discharge.

This distinction matters because you need to separate delays attributable to the hospital from those attributable to the insurer or TPA.

2. Stop treating every delay as the same problem

I would divide the discharge journey into four stages.

Stage A — Clinical discharge readiness

Doctor's discharge advice → final clinical documentation and bill readiness. Identify any delay in summaries, prescriptions, investigations or final billing.

Stage B — Submission completeness

Bill and discharge documents → formal submission to insurer/TPA. Establish whether the first submission is complete or whether repeated queries and resubmissions are creating avoidable delay.

Stage C — Insurer/TPA authorisation

Formal discharge request received → final approval issued. Track elapsed time, query frequency, pending cases and whether the three-hour regulatory timeline is exceeded.

Stage D — Physical departure

Approval → settlement, medication, transport and patient departure. Measure the residual time after approval. This is where a hospital can still have substantial operational control.

The reason for doing this is simple: if the hospital spends an hour preparing the bill and the TPA spends another three hours processing it, pressuring the TPA alone will not eliminate the entire delay.

3. If you have already tried everything, change the level of intervention

I would move beyond routine follow-ups and introduce three management-level interventions.

A. Make delays measurable and attributable. For every insured discharge, record the timestamps above, the insurer/TPA, the reason for each query, the time taken to resolve it, and the final departure time. Report the median and 90th-percentile delays, not just the average.

B. Escalate using evidence rather than individual complaints. Prepare a monthly insurer/TPA scorecard showing turnaround times, cases exceeding three hours after formal discharge authorisation requests, repeat queries and the resulting additional bed occupancy. Escalate persistent breaches through the insurer's designated grievance mechanism and, where appropriate, the IRDAI grievance channels.

C. Treat the residual delay as a capacity-management problem. Ensure that discharge documentation and billing are prepared as early as clinically appropriate. Have a defined escalation owner for pending approvals, and coordinate pharmacy, billing, nursing and patient transport so that the patient can leave promptly once the required authorisation and discharge formalities are complete. Do not compromise clinical clearance or applicable contractual and financial safeguards.

4. The business case: quantify the cost of doing nothing

At approximately 65 discharges a day, even a modest reduction in avoidable discharge time can be operationally meaningful.

For illustration, if 30 insured patients per day experience a delay that can be reduced by two hours, that recovers 60 bed-hours daily — equivalent to 2.5 bed-days of capacity per day.

That is not automatically 2.5 additional occupied beds or incremental revenue. The financial benefit depends on demand, bed type, admission timing and whether the released capacity enables another admission.

The calculation should therefore distinguish:

  • Capacity recovered: hours and bed-days released.
  • Revenue opportunity: additional admissions that the recovered capacity actually enables.
  • Direct savings: avoidable overtime, extended stay costs and other incremental expenses.
  • Patient experience: waiting time after clinical discharge readiness.

The objective is not to claim that every delayed discharge costs the hospital an entire day's revenue. It is to determine what the delays are genuinely costing and where intervention produces a measurable return.

One question before I recommend the next move

You mentioned that you have already tried everything. I don't want to give you another list of routine measures you've already implemented.

Where is the principal bottleneck today?

  • The TPA/insurer takes too long to issue final approval, even when documents are complete.
  • Repeated queries, document requests or deductions keep restarting the process.
  • The hospital also takes too long to complete billing and submit the discharge request.
  • It varies by insurer, patient and department; we cannot isolate one cause.

Which patients are most affected?

  • Cashless insurance patients only
  • Both cashless and reimbursement-related discharges

The answer determines whether the next step should be regulatory escalation, redesigning the insurer interface, or a more fundamental change in how discharge operations are managed.

If you want, I can:

  • Plan regulatory escalation for insurer delays beyond three-hour limit
  • Design process improvements addressing repeated queries and resubmissions
  • Optimize hospital discharge operations for billing and submission delays
0
Words to read
0
Minutes to read
0
Questions asked back
0
Drawings

What this answer gives a CEO

  1. ✕Lots of text. Most of it, a CEO already knows.
  2. ✕Advice for beginners, not for experts.
  3. ✕Experts need ideas beyond what they already know.
  4. ✕No real-life experience behind it.
  5. ✕To be useful, AI needs wisdom. Not just intelligence.
Tojo Discharge Process · 345-bed hospital, Kolkata

Tojo is reading

His own library, built from running real hospitals. Not the open internet.

  1. Discharge Process: where it usually breaks
    Reference · section 6
    Nothing starts until the doctor's order lands.
  2. Discharge Process: checking the real practice
    Reference · section 7.2
    Hospitals often hide insurance time inside their discharge time.
  3. Discharge Process: how the fix is built
    Reference · section 7.4
    Record every event from admission. The bill and summary build themselves.
  4. Bed Management: dead bed time
    Reference · section 7.3
    A bed stops earning once the bill is closed, even with the patient still in it.
  5. Discharge conversations that worked
    Playbook
    Name exactly what is broken.
  6. Hospital cases Tojo has worked
    Real hospitals, real outcomes
    Other hospitals won back 6 to 8 hours on each discharge.
0Questions Tojo needed to ask firstHe has seen this one before.
T
Tojo
Discharge Process

Don't accept it. Insurance is not why you are late. Your discharge starts too late.

Today the work starts only when the doctor says yes. Then the summary is typed, supplies are counted and the bill is made. The insurer gets the bill last, so it gets the blame. Three things keep it that way:

  • The bill and the summary are made after the decision, not built day by day.
  • Medicines and supplies are counted by hand before the bill can close.
  • Doctors' advice and notes are on paper, so someone types them up later.
Tap any stop on the two lines to see what happens there.
The doctor's yes should close the discharge, not start it.
Where shall we go next?
What is really wrong

Your discharge starts too late

TodayStarts when the doctor says yes
The Tojo wayStarts the day they are admitted
Tap any stop. All times are Example only.
Built from day one, not after the decision
About 16beds
Beds' worth of time won back every day
65 patients go home a day Your number × 6 hours earlier Tojo's guess ÷ 24 hours. 6 hours is the low end of what other hospitals won back. Not yet measured here.
A hospital CEO asks one question

Same question. Two answers.

First a generic AI on its top model. Then Tojo, who learned from running real hospitals.

906 words. Not one takeaway a CEO can use.

AI can't find the root cause without asking 100 questions. It has no wisdom.

A good doctor hears the symptoms and knows the problem. He knows what tests to run, what to treat and how to check it is working.

He does not ask 100 questions. He sees the pattern.

AI sees general patterns, not business patterns. It was never trained on real business data.

CEOs want an expert who knows many real businesses. One who says less and gets straight to the point.

Same question, same hospital

Now let us see how Tojo handles it

Not just a reply

Same question. Very different output.

  1. ✓Found the problem
  2. ✓Drew on hospitals with the same problem
  3. ✓Gave the fix
  4. ✓Showed what it changes
  5. ✓Showed how to do it

Side by side

Why it matters

Knowledge or wisdom

Generic AI

Knows what is written about hospitals. So it lists, hedges and asks questions.

Tojo

Knows what happens inside hospitals. Learned from real hospitals, real problems, real results. So he finds the cause and draws the fix.

CEOs want to talk to an expert who has run a hospital. Not to an encyclopedia.

What this answer gives a CEO
  1. ✕Lots of text. Most of it, a CEO already knows.
  2. ✕Advice for beginners, not for experts.
  3. ✕Experts need ideas beyond what they already know.
  4. ✕No real-life experience behind it.
  5. ✕To be useful, AI needs wisdom. Not just intelligence.

Inside Tojo’s Workspace

  • Step 1 of the simulation: one formula drawn as a wheel, with every measure the formula uses and which of them came from the hospital’s own files.
  • Step 2: setting targets. Seventy-five parameters, each with today’s value and a target you move, and a panel saying whether the targets add up.
  • Step 3: picking six KPIs. Six chosen cards across financial, operational, clinical, marketing and administrative, and the twenty-eight changes they bring into the simulation.
  • Step 4: simulating the plan. Each change marked not approved, achievable or dream, with its cost, and the running total, break-even month and KPIs on target along the top.
  • Freezing the plan: a dialog summarising twenty-four approved changes, total cost, break-even at month seven and three of six KPIs on target, to confirm.
  • Step 5: the plan month by month. Each approved change drawn as a bar from the month it starts to the month it is fully working, over the next thirteen months.

One chat agent, three personas

Same knowledge base. A different way of working with you.

Tojo the Listener

Ask, and be answered. Immediate replies drawn from the foundation skillsets — longer and denser than any general model gives you.

Tojo the Thinker

Ask why, and be shown. Opens the full skillset library, works the question through, and shows you the reasoning behind the answer.

Tojo the Strategist

Ask what to do, and be led. Reasons across every function at once and comes back with the course of action, owned end to end.

.03 — Strategy Layer

Play with your hospital’s future. Before you commit to it.

Not a projection sheet with a sensitivity toggle. A live mathematical model of one hospital — every tangible number and every intangible you can’t put in a cell: efficiency, time, ownership.

Step — 01 · Understand

Baseline, mapped

Every current metric and process, tangible and intangible, captured as-is.

Step — 02 · Simulate

Move the levers

Toggle decisions on or off, drag a value — the model recalculates instantly.

Step — 03 · Outcome

See the ripple

Revenue, occupancy, efficiency, ownership — every downstream effect, together.

The Point Of All This

Not more software.
One model that sees the whole business.

Tangibles and intangibles, in the same equation — updated the instant a decision changes.

Why This Isn't Just A Fancier Spreadsheet

Excel has sensitivity sheets. It doesn't have a model of you.

✕
Tangible metrics
Excel — Yes, revenue, cost, margin
Virevo — Yes, plus every downstream ripple
✕
Intangibles
Excel — Not represented
Virevo — Efficiency, time, ownership — modelled directly
✕
The model itself
Excel — Static formulas, manually rebuilt
Virevo — One living model of your whole business
✕
Scenarios
Excel — One at a time, by hand
Virevo — Infinite decision paths, instantly
✕
Memory
Excel — None — starts blank each time
Virevo — Learns from your unit's own history
✓
Bottom line
One model. Every variable. Updated live. That's the difference.
Proven In The Model
Every number here came out of the same mathematical model the Strategy Layer runs.
−0.5 DAYS ALOS+8.4% REVENUE LIFT+11 PTS OCCUPANCY+22 EFFICIENCY INDEX+31 OWNERSHIP SCORE6 WKS TO VALUE −0.5 DAYS ALOS+8.4% REVENUE LIFT+11 PTS OCCUPANCY+22 EFFICIENCY INDEX+31 OWNERSHIP SCORE6 WKS TO VALUE
DISCHARGE AUTOMATEDEVERY BED MAPPEDEVERY FUNCTION, DAILYOWNERSHIP CLONED DISCHARGE AUTOMATEDEVERY BED MAPPEDEVERY FUNCTION, DAILYOWNERSHIP CLONED

.04 — Execution Layer

Once a decision is made, Tojo doesn’t hand you a report — he runs it.

Custom automation for healthcare and hospitality first — built to run every department the way you would. Four proof points, each gets its own moment.

Proof — 01 · Discharge

Discharge, Automated.

ALOS down 0.5 days, 6–8 hours saved per discharge. Freed bed-days convert directly to ARPOB × Beds × 365 in recovered annual revenue.

Proof — 02 · Beds

Every Bed, Mapped.

100% next-day visibility across ward and ICU beds, mapped by 6 PM — not discovered when the ER is already backing up.

Proof — 03 · Cadence

Every Function, Daily.

No monthly surprises. Every department’s targets are checked today, not next quarter — the whole organisation, foolproof.

Proof — 04 · Ownership

Ownership, Cloned.

Every function performs as if the owner were standing in it personally — because in effect, Tojo is.

Where Virevo Runs Today
Built for healthcare and hospitality first. Four more industries queued.
HEALTHCARE — LIVEHOSPITALITY — LIVEMANUFACTURING — NEXTDEFENCE — NEXTRETAIL — NEXT HEALTHCARE — LIVEHOSPITALITY — LIVEMANUFACTURING — NEXTDEFENCE — NEXTRETAIL — NEXT
Live Now
HealthcareHospitality
Same Tojo — swipe to compare tiers →
05
.05 — Pricing

Software as a Service. Service as a Software.

One simple model across every tool: pay monthly, cancel anytime. We're confident enough in Tojo that once your team runs on him, you won't go back to your old ERP — or a generic chatbot.

Save up to 40%

Chat plans are priced per month and run on credits — the three levels consume credits at different rates, in proportion to the depth of skill asked of them. USD rates shown alongside are the international list price; Indian customers are billed in rupees at the rate shown. Annual plans are billed once, twelve months ahead.

Enterprise Products
Product 02 — Enterprise

Business Mapping & Decision Simulation

Your entire business, mapped and modelled — tangibles and intangibles alike. Scoped and priced per unit, per module.

Get a Quote →
Product 03 — Enterprise

Decision Implementation & Automated Operations

Custom-built automation for your departments, integrated with your existing systems. Scoped and priced per unit, per module.

Get a Quote →