~4% Of expected revenue never arrives
A 2.7% final denial rate on top of 1.3% bad debt. Both are recoverable in part, and both are treated as the cost of doing business.
Healthcare ยท India & South Asia
You are spending nineteen billion dollars a year reworking claims you already earned.
Denials are not a billing problem. They are a documentation problem that surfaces as a billing problem.
$48.4B
of hospital revenue lost to denials and uncollected bills in one year, up 25 percent.
Source: Kodiak Solutions, State of the healthcare revenue cycle
In India
This is what it actually runs on here.
Platforms in this market
- ABDM and ABHA
- Insta HMS
- Attune
- Medixcel
- PMJAY claim portals
Rules that apply here
- the DPDP Act 2023
- NABH
- ABDM health data standards
- NHA claim rules
We read the rule before the call. It is the cheapest way to prove we did the work.
What is happening
The claim was right the first time. It just could not prove it.
$57 Per reworked claim, and you rework a lot of them
US hospitals spend roughly $19.7 billion a year overturning denials. The cost is almost entirely staff time.
+12-14% Denied claim values are climbing
Average denied inpatient claim value rose 12% and outpatient 14% in one year, alongside rising audit volume.
The evidence exists but is not where the claim is
Medical necessity lives in physician narrative and nursing documentation. Your claims system holds structured fields. Bridging the two is manual, every single time.
However hard, whatever it is
Denials are one example. Bring the one that is actually costing you.
This page happens to be about appeals. If your problem is theatre scheduling, bed flow or a report nobody trusts, we start in exactly the same place.
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01 We sit with you
Days where the work happens, not a workshop in a meeting room. We watch the job get done and write down the shortcuts nobody wrote down.
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02 We read everything
Your data, your rules, your vendors and their documentation, and the published research on your sector. We report what is actually in there.
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03 We break it to first principles
Not which tool fixes this. What is actually causing it, taken apart until we reach the piece that cannot be divided further.
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04 Then we build
Weeks, not quarters. By this point we are not guessing what to build, and guessing is the thing that makes projects long.
Where we sit
Your EHR stays. We build the work that happens around the chart.
4
What you get
- Denials Appeal packets assembled, not researched
- Prevention Denial risk flagged before submission
- Visibility Denial performance by payer, service line and physician
3
Built new for you — none of this exists in your stack today
- An appeal pack that assembles itself from the chart
- A denial board the team stands at every morning
- A bedside tag that says when a check last happened
2
The revenue-cycle layer Reads the chart. Writes nothing into it that you have not approved.
Connectors, one agreed meaning per field, and a model reading what no
field holds. Accuracy measured on your own records.
1
- ABDM and ABHA
- Insta HMS
- Attune
- Medixcel
- PMJAY claim portals
What you already run — unchanged, and still yours
If it is in the chart, we can reach it. HL7 v2, FHIR, an interface engine, a scanned consent form. We have built against all four.
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No API -
No documentation -
A terminal from 1994 -
It arrives as paper -
The vendor said no -
It reports nothing
Not a list of limits. Name yours on the call.
And once we can reach it, a model can read it. Most of the value here is in the sources nobody ever structured — the note, the letter, the screen.
Intelligence, plumbed in
A denial letter and a chart are both text. Both can be read.
The work is HL7 and FHIR plumbing, one agreed meaning per field, and an eval set of appeals your team already won.
How we make AI survive real data-
Connectors -
A semantic layer -
Evals you can check
What changes
Judge us on this, not on what we built.
Denials Appeal packets assembled, not researched
The clinical evidence pulled from the record, matched to the payer's stated reason, formatted to that payer's requirements.
Prevention Denial risk flagged before submission
Patterns from your own denial history, applied to claims that have not gone out yet. The cheapest denial is the one that never happens.
Visibility Denial performance by payer, service line and physician
So the conversation with a payer is evidence-led, and so you know which fights are worth having.
Who this is for
The people who feel this first
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VP Revenue Cycle -
Director of Patient Financial Services -
CFO -
Chief Medical Information Officer -
Director of HIM
Straight answers
The questions you would ask on the call
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We already have a revenue cycle vendor. Where do you fit?
Underneath them, usually. Billing platforms and RCM vendors are built to submit claims and follow up on status. The work that does not get done is arguing a denial, because that means reading the medical record rather than querying a database. That is the gap we build into.
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Do you replace our EHR?
No, and you should be suspicious of anyone who suggests it. We build the operational layer on top of the system of record you already have.
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How do you start?
A free call, then a proper look at your data. We come back with your real denial and appeal numbers, what you can recover, and whether a build is worth it. If it is not, we say so.
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Can AI draft appeals from the chart?
It assembles the evidence and drafts a first version. A person signs every one. We score the drafts against appeals your team already won.
Do you know the rules that apply in India, Sri Lanka and Bangladesh?
For hospitals that means the DPDP Act 2023, NABH, ABDM health data standards and NHA claim rules. We read the rule before the call, so the first meeting is about your operation rather than about us catching up.
Whatever hospitals needs here, we can make it.
What you already run stays where it is. Around it we build software, hardware and the process itself. Here that means an appeal pack that assembles itself from the chart.
See everything we build-
Software -
Hardware -
Ways of working -
Whole ventures
Honest about the numbers
The figure above is from Kodiak Solutions, State of the healthcare revenue cycle, for hospitals.
We have not localised it, because a number nobody can check is worth less than a real one plus this sentence. The pattern travels. The size of it in your market is a question for the call.
Same industry, other markets