The Future of Malaria Diagnostics

Never a
slide too far.

Edge AI diagnostics for peri-urban laboratories across Africa. 100% offline. Affordable. Deployable anywhere.

Riascope device — real product render
Product video placeholder
Nigerian Patent FiledRegistered CompanyTony Elumelu Foundation Grant WinnerProject I2M Grant Winner

Fast

Under 10 minutes, slide to result

Manual microscopy takes 45+ minutes and depends on a tired technician's eye. Riascope's edge AI reads the same slide in under 10 — 4.5x faster, every time.

Riascope drying module detail

Simple

Built for peri-urban labs, not sterile trial rooms

No specialist microscopist, no reliable power grid, no fibre internet required. Riascope is designed around the realities of the clinics that see the most malaria cases.

Children in a peri-urban Sub-Saharan African community

Offline-First

Works anywhere, no internet required

100% offline edge inference means Riascope runs the same in a Lagos hospital as it does in a primary health centre three hours from the nearest cell tower.

Riascope device — real product render

Where We Stand

Honest Progress

MVP Built

Working prototype — Raspberry Pi runs the core AI detection pipeline.

Nigerian Patent Filed

IP protection filed for the Riascope diagnostic system.

Registered Company

Riascope Limited is a fully incorporated entity.

Grants Won

Tony Elumelu Foundation & Project I2M grant winner.

The Process

How It Works

01

Fast-Dry Slide

Forced-air drying module preps up to 10 slides in under 3 minutes.

02

Mount Slide

Place the dried slide on the manual X-Y stage.

03

Guided Scan

Step-by-step battlement scan pattern guides the optics across the smear.

04

AI Detects

Real-time parasite detection and count in under 10 minutes.

Who We Serve

Hospitals

High-volume diagnostic departments.

Private Laboratories

Commercial testing facilities.

Primary Health Centres

Government & community clinics.

The People

Building Riascope

Adeleke Eniola

Adeleke Eniola

CEO / Founder

Business strategy, partnerships, and project leadership.

Emelife Tobechukwu

Emelife Tobechukwu

CTO / Technical Lead

Hardware design, system architecture, and development.

UE

Ubongabasi Etim

ML Engineer

AI model development, training, and optimization.

AB

Alfred Bidokwu

ML Engineer

AI model development, training, and optimization.

AE

Ajao Emmanuel

Cell Biologist

Microscopy implementation, parasite identification, scientific guidance.

BB

Dr. Babajide Bamiro

Clinical Advisor

WHO-certified malaria microscopist & Chief Medical Lab Scientist.

Join the Fight
Against Malaria

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Questions

Frequently Asked Questions

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