Frequently Asked Questions

PearMedica is a B2B SaaS API platform providing AI-powered medical intelligence specialised for African diseases. Our API enables hospitals, HMOs, telemedicine providers, and healthcare applications to integrate intelligent symptom assessment and triage capabilities.

Common use cases include: patient triage kiosks, telemedicine pre-consultation flows, 24/7 symptom checkers for mobile health apps, clinical decision support tools, and automated nursing intake forms.

We target >85% accuracy on African disease assessments validated by our Chief Medical Officer. The system uses a 5-layer validation pipeline including hallucination detection, emergency pattern matching, and WHO guideline compliance checks.

The API is designed for <500ms p95 response time. Typical assessments complete in 300–500ms. Complex multi-condition differentials may take slightly longer due to additional reasoning.

Yes. Our Pilot tier includes 200 free assessments per month with full API access. This is designed for evaluation and early-stage integration development.

PearMedica uses tiered pricing: Pilot (free, 200 assessments), Professional (₦120,000/month, 1,000 included), and Enterprise (custom volume). See our Pricing page for current details.

The Pilot tier is intended for evaluation and low-volume use. For production deployments, we recommend the Professional or Enterprise tier for higher quotas, SLA guarantees, and priority support.

The API is language-agnostic — any language that can make HTTP requests works. We provide code examples in JavaScript/TypeScript, Python, PHP, and cURL. SDK packages are planned for post-MVP.

Set the X-Interview-Id header to track a multi-turn session. The API returns a "next_question" object with follow-up questions. Continue calling /v1/assess with accumulated evidence until "should_stop" is true.

The /v1/health endpoint reflects real-time status. If the AI provider is unavailable, the API returns a 503 with a clear error message. We recommend implementing a circuit breaker pattern and fallback UI.

Yes. Use a test API key (prefixed with sk_test_) to make sandbox calls that return mock data without consuming your quota.

The knowledge base covers 200+ conditions prevalent in Africa, including malaria, typhoid, Lassa fever, cholera, yellow fever, and more. For MVP, 30 conditions are fully modelled with detailed diagnostic rules.

Yes. All medical content goes through a 10-step development process: scope definition, expert knowledge elicitation, peer review, clinical case assembly, expert review, technical review, regression testing, manual testing, translation updates, and deployment.

Medical content is updated continuously based on WHO guideline changes, regulatory updates, pilot feedback, and monthly PubMed literature scans. Updates go through CMO review and A/B testing before production deployment.

Yes. Our symptom alias system includes region-specific terms (e.g., "feeling hot-hot" maps to fever, "body dey pain" maps to generalised body aches). This ensures accurate symptom capture from patients using local language.

During the MVP phase, all data is synthetic. In production, assessment data is stored securely with encryption at rest (AES-256) and in transit (TLS 1.2+). We follow NDPA 2023 compliance requirements.

MVP infrastructure runs on Supabase (managed PostgreSQL). Post-funding, production data will be hosted on Nigerian colocation providers (MainOne/Rack Centre) for NDPA compliance before processing any real patient data.

PearMedica is designed with compliance in mind. We implement encryption, audit trails, access controls, and minimal data retention. Formal HIPAA certification is on our post-MVP compliance roadmap.