Transform Healthcare Delivery with AI-Powered Voice Triage
Sauti Care reduces emergency wait times by 30%, detects critical cases in 2 minutes, and prevents millions in fraud—all through intuitive voice interaction in Swahili and English.
Kenya's Healthcare Crisis
A perfect storm of workforce shortage, diagnostic inaccuracy, and systemic fraud threatens healthcare delivery for 55+ million Kenyans.
Healthcare Workforce Crisis
Only 19 doctors per 100,000 people—5x below WHO recommendations
Diagnostic Inaccuracy
Only 20% of providers correctly diagnose common conditions
Insurance Fraud Hemorrhaging
Sh50+ billion lost annually to fraudulent claims
Wait Times
Average 2-hour emergency room wait in public hospitals
The Sauti Care Solution
A unified platform combining voice AI, medical diagnostics, and fraud prevention to transform emergency care delivery.
Voice-First Interface
Multilingual speech recognition in Swahili, English, and local languages—no typing required
Real-Time Triage
AI-powered ESI triage algorithm with 98.21% accuracy classifies patients in seconds
Medical Imaging AI
Chest X-ray analysis detecting TB, pneumonia, COVID-19 with 94% sensitivity
Fraud Detection
Ensemble ML model identifies 5-10% of fraudulent insurance claims in real-time
Automated Records
Voice input automatically creates digital health records with zero manual data entry
SHA Integration
Direct API integration with Social Health Authority for seamless claims processing
Hybrid Cloud-Edge Architecture
Cloud-based training and processing with edge deployment at healthcare facilities ensures <30ms latency, offline capability, and compliance with Kenya's data residency requirements.
Measurable Impact
Rigorous impact evaluation across 5 facilities tracking clinical outcomes, operational efficiency, and financial returns.
Wait Time Reduction
From 180 mins to 126 mins
Critical Case Detection
Within 2 minutes of arrival
Documentation Time Cut
From 15 mins to 7.5 mins per patient
Fraud Detection Rate
Real-time insurance claim analysis
Fraud Prevention (Medium-term)
In first 8 months of deployment
Healthcare Worker Adoption
Pilot facility target
Revenue from fraud prevention alone
Break-even timeline post-project
Cost per patient triaged (vs Sh150 traditional)
Proven Technology
Built on state-of-the-art open-source foundations with proprietary optimization for African healthcare contexts.
Wav2Vec 2.0
8.3% WER Swahili speech recognition
Multilingual BERT
Medical symptom extraction & NLP
Random Forest + XGBoost
98% fraud detection accuracy
CNN
94% accuracy chest X-ray analysis
TensorFlow Lite
Edge deployment <200ms latency
FHIR R4
Interoperable health data exchange
Strong Partnerships
Collaboration between Kenya innovation leader and world-class medical AI expertise from King's College London.
iWorld Afric
Kenya-based AI innovator with 12+ completed ML projects and 5 healthcare deployments. CTO leading government digital health initiatives.
- Project management & local implementation
- Stakeholder & healthcare facility relationships
- SHA & government integration
King's College London
World-leading AI Centre with £10M annual budget, 50+ researchers, and partnerships with 15 NHS trusts. 500+ published papers on AI in healthcare.
- Validated chest X-ray AI models (94% accuracy)
- Clinical validation methodology & standards
- Global best practices & research collaboration
Strategic Ecosystem
Ready to Transform African Healthcare?
Join leading healthcare institutions, government partners, and impact investors in building the future of emergency care in Kenya and beyond.
Initial project timeline
Total investment required
Per investor check size