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.
See Sauti Care in Action
Watch an end-to-end clinical workflow: Registration, AI-assisted Voice Triage, and Doctor routing seamlessly integrating in real-time.
Reception
Digital induction with ID and SHA check.
AI Triage
Nurse captures vitals and spoken symptoms.
Doctor Encounter
Clinician reviews synthesized AI insights.
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 ÂŁ10M 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
