Technology & infrastructure
AI infrastructure
built for clinical trust.
Four AI models, AWS healthcare-grade infrastructure, and NVIDIA GPU acceleration — working together to deliver triage decisions clinicians can rely on and patients can trust.
AI technology
AI isn't a feature here. It's the entire care pathway.
Four models work in concert — each audited, each with a human reviewer in the loop, each improving weekly on confirmed outcome data.
Multilingual symptom understanding
A fine-tuned large language model trained on de-identified consultation transcripts from African clinical settings and WHO clinical guidelines. The model conducts structured symptom intake in English, Pidgin, Yoruba, Hausa, Igbo, and Swahili — adapting follow-up questions based on prior answers.
Risk stratification engine
A gradient-boosted ensemble model that scores symptom severity across 14 clinical axes — including 23 red-flag patterns associated with cardiac events, stroke, sepsis, and obstetric emergencies. Output is a four-tier risk classification reviewed by a CMO-approved decision framework.
Clinician matching via vector search
Practitioner embeddings encode specialty, sub-specialty, languages spoken, real-time availability, and aggregated patient outcome scores. FAISS-powered vector similarity search returns a ranked shortlist in under 200ms — updated daily as clinician availability changes.
Continuous outcome learning
Every confirmed diagnosis and clinician note is fed back into the training pipeline — de-identified and consented. Models are retrained weekly. Each retraining cycle is audited against a held-out clinical benchmark before deployment.
Cloud — AWS
Healthcare-grade cloud backbone.
Every AWS service in our stack was chosen specifically for healthcare compliance — HIPAA-eligible, NDPR-compatible, with audit trails on every access event.
Managed LLM inference with no model weights leaving the VPC. Powers symptom understanding and multilingual response generation.
Containerized backend APIs — autoscaling, no server management, isolated per-service security boundaries.
Encrypted relational store for patient records. Field-level KMS encryption. PITR backups with 35-day retention.
Async clinical workflows: risk-score post-processing, notification dispatch, model feedback ingestion.
De-identified training data storage with server-side encryption and object-level access logging.
Global CDN edge delivery with managed WAF rules — rate limiting, bot detection, SQL injection and XSS protection.
MFA-enforced authentication with PKCE OAuth flows. No passwords stored in application code.
Full audit logging on every API call. GuardDuty detects anomalous access patterns and potential data exfiltration.
AI acceleration — NVIDIA
Real-time inference. No queue.
Triage decisions need to feel instant. NVIDIA's inference stack lets us serve multiple concurrent AI models with sub-100ms latency — at the scale Africa demands.
Multi-model GPU serving for concurrent inference requests. Supports TensorRT, ONNX, and PyTorch backends on a single server fleet.
Quantized and optimized model graphs for sub-100ms triage inference at peak load — even on single-GPU instances.
Multilingual speech recognition for Pulsa's voice triage channel. Fine-tuned on West African English and Pidgin phoneme datasets.
Medical imaging AI framework on the roadmap for radiology report summarization and imaging-informed triage.
Portable, secure model deployment containers that keep inference workloads cloud-agnostic and reproducible across regions.
Security & compliance
Data protection is the product.
Field-level KMS encryption on all patient records. Keys rotated annually.
All API calls encrypted end-to-end. No cleartext health data on the wire.
Nigeria Data Protection Regulation compliant. Data subjects can export or delete at any time.
Controls mapped to HIPAA Security Rule. Annual third-party audit planned for Series A.
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