Wudouh · Pitch Deck
Healthcare · DIAGNOSTIC IMAGING
Wudouhوضوح
Triage-grade vision for chest, head, breast, and skin — radiologist always signs.
neuriya.ai — Sovereign, Arabic-first enterprise AI
Problem
The most critical scan waits in line behind whatever was acquired first
- Chest X-ray, CT head, mammography, and dermatology studies queue in acquisition order, so a critical finding can sit behind routine studies for hours.
- Radiologists have no confidence-scored signal on which study in the queue needs attention first — urgency is judged only once a study is opened.
- Critical and urgent findings have no tracked response-time target, so there is no way to know whether the department is actually meeting a safe read-time.
- Departments already run large PACS estates, but adopting new AI tools usually means a separate viewer and a disrupted worklist, not a drop-in addition.
Solution
One pipeline re-orders the worklist so the critical study is always next
Product
Wudouh in action
How it works
From first touch to outcome
Capture
Studies flow in from connected modalities across chest, head, breast, and skin imaging.
Score
Computer-vision models score each study for urgency within minutes of acquisition.
Re-prioritize
The worklist reorders automatically, putting critical and urgent studies ahead of routine ones.
Sign off
A radiologist reviews every flagged finding and confirms or corrects it before it becomes a report.
Market
Sizing the opportunity
- TAM — $1.3B. MENA AI-assisted diagnostic imaging market
- SAM — $160M. Saudi radiology AI triage software market
- SOM — $10M. 3-year obtainable share via design-partner radiology departments
Radiologist supply isn't growing at the same pace as imaging volume across Saudi hospitals, and Vision 2030's healthcare-capacity expansion is only widening that gap — making worklist triage that runs on a department's existing PACS an easy budget case rather than a discretionary tool purchase.
Business model
How Wudouh makes money
Per-study volume subscription
Priced by monthly study volume across the modalities under active triage.
Per-modality module pricing
Recurring fee per imaging modality enabled — chest, head, breast, or dermatology — so departments can start narrow.
Implementation & PACS-integration fee
One-time fee for PACS and modality worklist integration and site-specific model calibration.
Revenue streams
Where the revenue actually comes from
Competition
Where we win
Our edge
- Multi-modality triage in one pipeline — chest, head, breast, and skin — instead of separate point solutions per modality.
- Mandatory radiologist sign-off with a calibrated confidence score on every finding, keeping diagnostic authority with the specialist by design.
- PACS-native integration means no separate viewer and no disrupted worklist — the department's existing infrastructure does the work.
- Founding team combines Saudi enterprise delivery experience with computer-vision engineering built for diagnostic imaging.
Traction
Engineered and waiting on its first PACS connection
- The imaging triage product is built end-to-end: triage dashboard, re-prioritized worklist, study log, and case review, ready to connect rather than still being designed.
- Architecture pre-aligned to PDPL, NDMO Classification, MoH Standards, HL7 FHIR R4, and ISO 27001.
- Actively selecting design-partner radiology departments for a first imaging triage pilot cohort.
Go-to-market
One modality first, full department coverage once the SLA holds
- 1Land with 1-2 design-partner radiology departments, starting on a single high-volume modality such as chest X-ray.
- 2Prove time-to-sign-off improvement on critical findings over a pilot quarter against the department's existing worklist order.
- 3Expand to additional modalities within the same department, then to affiliated facilities within the hospital group.
Team
Built by operators, not just builders
The ask
Raising a seed round to connect the first PACS and prove the SLA
We're raising to fund multi-modality model validation, PACS integration tooling, and the core clinical and engineering team through first-revenue pilot deployments.