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Answers to common questions about the PearMedica API, pricing, medical content, and data privacy.
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.
Both — built on one clinical engine (PearMDx). Developers integrate the API directly, while hospitals use the full PearCare EHR with the same engine built in. See the /pearcare page for the hospital platform.
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.
Our target is >85% accuracy on African disease assessments, with clinical standards set and reviewed by our medical review team. This is a target we are validating toward, not a guaranteed result. The system runs every output through a 6-layer validation pipeline including hallucination detection, emergency pattern matching, and WHO guideline compliance checks.
Assessment is an AI reasoning task, not a simple lookup, so responses are not instantaneous — a typical end-to-end assessment can take tens of seconds, and complex multi-condition differentials may take longer due to additional reasoning. Reference-data lookups (symptoms, conditions, lab tests) return quickly. We recommend showing an interim loading state and implementing sensible request timeouts.
Our Pilot tier at ₦150,000/month includes 200 assessments and 1,000 PearMDx Chatbot queries. It is designed for evaluation and low-volume clinical use with full API access.
PearMedica uses tiered pricing: Pilot (₦150,000/month, 200 assessments + 1,000 PearMDx Chatbot queries), Professional (₦420,000/month, 2,500 assessments + 1,000 PearMDx Chatbot queries), and Enterprise (custom volume). Only AI assessments are billed — all reference data lookups are free and unlimited. 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, Python, and cURL, plus a published OpenAPI 3.1 spec you can use to generate a client in your own stack. Pre-built, installable SDK packages are on the roadmap 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.
For MVP, 30 conditions prevalent in Africa — including malaria, typhoid, Lassa fever, cholera, and yellow fever — are fully modelled with detailed diagnostic rules. The knowledge base is curated for African disease burden and is expanding toward broader coverage over time.
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 clinical 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.