AI Research

Rigorous
clinical science.

Clinically-grounded language models. Privacy-preserving architectures. Academic-grade research deployed at scale across Africa.

Our Principles

How we build
responsible AI

Every Syncorix model is developed against a set of non-negotiable research standards — accuracy, equity, privacy, and clinical validity.

01

Clinical grounding

All models are validated against African disease prevalence data — tropical conditions, endemic infections, and nutritional profiles that Western training sets miss.

02

Privacy-first architecture

Zero-ingestion pipelines, Safe Harbor de-identification, and privacy-preserving longitudinal linkage. Patient data never moves.

03

Global interoperability

FHIR R4, LOINC, ICD-10/11, OMOP CDM — every dataset and model output adheres to international standards demanded by global research buyers.

04

Equity by design

Models are tested for demographic parity across age, gender, and geography. We measure and publish disparity metrics before clinical deployment.

05

Human oversight

Every AI recommendation is advisory. Clinicians retain authority. We build systems that augment professional judgment, never replace it.

06

Audit transparency

Governance decisions, de-identification actions, and model performance metrics are logged in immutable audit ledgers available to facility partners.

Active Research Areas

What we're
working on.

Four open problems our team is pushing forward right now.

Clinical NLP

African medical language models

Fine-tuning large language models on African clinical narratives, local languages, and pidgin to improve diagnostic accuracy, interpret region-specific diseases, and deliver context-aware AI for safer, scalable healthcare.

Pharmacy AI

OTC drug safety at scale

Predicting adverse drug events and interactions in low-resource pharmacy settings — accounting for polypharmacy in patients without formal medical records.

Data infrastructure

Privacy-preserving longitudinal linkage

Reconstructing patient journeys across fragmented EMR systems without processing identifiers — enabling cohort research at population scale.

Claims AI

Fraud detection in emerging markets

Training fraud detection on Africa-specific claims patterns that differ substantially from Western fraud typologies used in commercial solutions.

Compliance Stack

Regulatory
foundation.

Every model and pipeline is designed around these standards from day one.

NDPA 2023
Nigeria Data Protection Act — the law governing patient records, secondary use, and cross-border transfers.
NHA 2014
National Health Act — confidentiality obligations and lawful basis for health data processing.
HIPAA Bridge
US HIPAA-aligned controls enabling international research partnerships and global buyer acceptance.
FHIR R4
HL7 standard for structured clinical data exchange and linkage.