Fewer rejections.Fewer prior authorizations.Lower costs.
AI does the routine checks. The physician decides, and the insurer keeps final authority.
The scale of it
Saudi healthcare loses billions to claims that could have been right the first time
15–25%
Of claims are rejected across Saudi healthcare providers
Figures from published market studies and sector reports. The clinical share of rejection reasons comes from our own site visits and interviews with clinics.
The challenge
Four gaps drive rejections, rework and delay
Claims do not fail at random. The same four breakdowns repeat across Saudi clinics and insurers, and almost all of them are visible long before a claim is ever submitted.
Closing them is not a matter of arguing harder after a decision comes back. It is a matter of getting the claim right while the clinical context is still in the room.
Documentation gap
Clinical intent gets lost in complex coding. The rework begins before the claim is even sent.
Visibility gap
Clinic and payer data sit in separate systems and get stitched together by hand, so nobody sees the pattern.
Review gap
Reviewers work through high volumes under time pressure, and providers get rejection reasons too vague to act on.
Communication gap
Pre-authorization decisions are chased through fragmented channels that no one can track.
Patients wait longer for care. Clinics lose revenue they have already earned. Insurers pay for manual review that better evidence would have made unnecessary.
The platform
One neutral layer between the two sides of every claim
Provider tools push for payment. Insurer tools push back. Nabdah sits between them and works from the same clinical evidence, so both sides improve at once.
Healthcare providers
- SendsClean, evidence-based claims
- GetsGuidance while documenting, and fewer rejections
Nabdah
A neutral, governed layer. It organises the clinical evidence, checks it against approved criteria, and gives each side what it needs.
Insurance companies
- GetsCleaner claims with the evidence attached
- ReturnsFaster, more consistent decisions
Why neutrality matters
A provider-only tool can end up defending claims the clinical evidence does not support. An insurer-only tool can end up refusing claims that it does. One shared, evidence-based loop is the only version where stronger claims and fairer reviews are the same outcome.
What the platform does
Four capabilities, one shared loop
Not four separate tools. Each capability feeds the same engine, and every claim outcome sharpens the next recommendation.
AI-assisted claim guidance
Helps physicians strengthen documentation and coding before submission, while the clinical context is still in front of them.
Clinic claims analytics
Surfaces the patterns behind denials and the revenue leaking through them, so clinics fix the cause instead of the symptom.
AI clinical claim review
Reviews each claim against approved criteria and flags missing evidence, supporting insurer reviewers who keep final authority.
AI pre-authorization support
Checks that each request is complete, clinically justified, and meets the criteria agreed with the insurer.
One governed engine underneath all four: the same clinical evidence, the same approved criteria, the same feedback from real outcomes.
How it works
The check happens while the clinical context is still there
Nabdah works at the moment of documentation, not after a decision comes back.
The physician documents the encounter
Care is recorded the way it always has been: the diagnosis, the services, the medications, and the clinical reasoning behind them.
Nabdah checks it in the moment
Documentation completeness, diagnosis-to-service consistency, diagnosis-to-medication consistency, coding quality, clinical justification, and claim readiness are all checked against approved criteria before anything is sent.
The physician accepts, edits, or rejects
Every recommendation is a suggestion. Nothing changes in the record unless the physician decides it should, and every decision is logged.
The claim goes out, and the outcome comes back
The insurer receives a claim with its evidence attached. What happens next returns to the platform: approved or rejected, and how long it took. Each outcome sharpens the next recommendation.
Follow-up visit · 3 service lines
The physician documents the encounter
Care is recorded the way it always has been: the diagnosis, the services, the medications, and the clinical reasoning behind them.
Follow-up visit · 3 service lines
Nabdah checks it in the moment
Documentation completeness, diagnosis-to-service consistency, diagnosis-to-medication consistency, coding quality, clinical justification, and claim readiness are all checked against approved criteria before anything is sent.
Follow-up visit · 3 service lines
- Documentation completenessClear
- Diagnosis-to-service consistencyNeeds a note
- Claim readinessNeeds a note
Suggestion
The physician accepts, edits, or rejects
Every recommendation is a suggestion. Nothing changes in the record unless the physician decides it should, and every decision is logged.
Follow-up visit · 3 service lines
- Documentation completenessClear
- Diagnosis-to-service consistencyNeeds a note
- Claim readinessClear
Suggestion
One billed service is not supported by the recorded diagnosis. Add the clinical finding that justifies it, or remove the line.
The physician decides
The claim goes out, and the outcome comes back
The insurer receives a claim with its evidence attached. What happens next returns to the platform: approved or rejected, and how long it took. Each outcome sharpens the next recommendation.
Follow-up visit · 3 service lines
- Documentation completenessClear
- Diagnosis-to-service consistencyNeeds a note
- Claim readinessClear
Suggestion
One billed service is not supported by the recorded diagnosis. Add the clinical finding that justifies it, or remove the line.
The physician decides
Returns to improve the next recommendation
The feedback loop
The loop a one-sided tool cannot close
A provider tool watches claims leave. An insurer tool watches claims arrive. Neither sees the whole circuit, so neither can learn from it.
Evidence organised
Nabdah structures the clinical evidence behind the claim and checks it against clinical and approved criteria.
Human validation
Physicians and reviewers validate what the platform proposes. People decide; the system supports.
Approved pathway
The claim or request follows the permitted workflow, with every step recorded.
Real outcomes
Approvals, rejections, payments and turnaround times come back as signal rather than guesswork.
Better guidance
What the loop learns from one claim improves the guidance on the next one.
Every claim makes the platform better at the claim after it.
What sets us apart
Most tools check the form. Nabdah checks the medicine.
Between 70 and 80 percent of rejection reasons are clinical, yet most existing systems check technical fields: identifiers, formats, eligibility flags. That leaves the majority of the problem untouched.
Reads each insurer's real behaviour
Rejection patterns differ by payer. Nabdah learns from what actually gets rejected, not from a static rulebook.
Warns before the claim is sent
The moment to fix a claim is while the physician still has the case in mind, not weeks later.
Evaluates full clinical context
Checked against Saudi and international clinical guidance, not just field validation.
One platform, both sides
Cleaner claims for providers and faster reviews for insurers come out of the same loop.
AI checks, humans decide
Routine verification is automated. Clinical judgement is not, and every recommendation is logged.
Why now
The control layer the market is about to need
Prior authorization is being unwound
Removing pre-authorization speeds care up, and without a control layer it lets cost inflation in. Independent verification of claims and requests is what makes the removal safe.
Proven elsewhere, absent here
Platforms built on this exact model of clinical review at scale, with decisions returned in real time, are established in mature healthcare markets. Our market research has not found an equivalent operating in Saudi Arabia.
The infrastructure already exists
A unified national claims platform and standardised clinical coding mean the data arrives in one shape. This kind of AI can be deployed here faster than in markets still stitching systems together.
Value-based care is the direction
Connecting clinical decisions to claim quality and reimbursement outcomes is exactly the shift Saudi Vision 2030 is driving toward.
Trust and governance
Built to be trusted by both sides
Data stays in Saudi Arabia
Processing happens on servers inside the Kingdom.
No identified patient data stored
Identifying details are removed, and the platform works from the clinical and coding content of the encounter.
Aligned with the data protection law
Personal data is handled with the least processing necessary, for the stated purpose only, in line with the Personal Data Protection Law.
The human decides
Physicians accept or reject every recommendation, insurer reviewers keep final authority over complex cases, and every decision is logged.
Nabdah makes no claim of formal certification or regulatory approval. These are the commitments the platform is built on.
Where we are
Past the idea stage
A working product, built on real claims data and shaped by the clinics using it.
15,000
Historical claims processed
25,000
Individual service lines processed
8
Clinics contributed de-identified historical data
Figures reflect work completed to date.
FAQ
What clinics and insurers ask first
Fewer rejections start before the claim is sent
We are working with clinics and insurers who want cleaner claims and faster decisions. Tell us about yours and we will show you what the platform sees.