While the world invests to make machines smarter, we invest in machines that make people smarter.
We're building a real-time knowledge intelligence engine — and it starts with medical education.

Born from raw reality.
EOSIA HEALTH is not the product of a theoretical concept born on paper, but the fruit of a direct confrontation with reality on the ground. Entering medical school, driven by a deep love of technology more than by the classic calling, I ran into a wall: rigid teaching methods, fragmented resources, and that dizzying feeling of being left entirely to myself.
That initial shock became the catalyst for a transformation. What followed was a four-year endurance run of intense self-taught learning and pure resilience. While I absorbed the medical sciences by day, I spent my nights taming code — going from barely mastering a word processor to architecting the entire technological ecosystem that would change everything.
Out of that twofold struggle came a mission with no compromise: to turn the student's vulnerability into strength, and to redefine how future doctors learn, engage, and succeed. We are not just building a tool; we are building the confidence of those who will heal tomorrow.
More than grades.
MyQCM is an AI-powered adaptive learning platform built to improve medical education in Algeria through personalization, bilingual support, and a learning economy that gives real value to student effort. It is meant to do more than raise grades — it helps build better-trained, more motivated doctors, supports the local education system, and creates a sustainable Algerian solution with real national impact.
Learn better
Adaptive learning, personalized to each student's knowledge state.
Bilingual
In French and Arabic, built for the Algerian context.
Learning economy
Student effort earns real value.
National impact
A sustainable Algerian solution, from first year to résidanat.
From MyQCM to EOSIA.
Over time, MyQCM grew from a small AI app into a large neuro-symbolic ecosystem. That's why MyQCM became EOSIA.
- 1
AI app
A first app for revising differently.
- 2
Adaptive platform
Adaptive MCQs, smart articles, coaching.
- 3
Neuro-symbolic ecosystem
An engine connecting content, learner, memory and assessment.
- 4
EOSIA
The knowledge intelligence engine.
What EOSIA really is.
EOSIA is a domain-adaptive knowledge intelligence engine. It transforms raw learning content into measurable knowledge structures, observes how people interact with that knowledge, estimates concept mastery and memory decay, calibrates assessment quality from behavioral data, and distributes personalized training in real time.
EOSIA is building a real-time knowledge intelligence engine. It converts content into Knowledge Components, measures learner state from behavior, calibrates assessment quality, and uses AI agents to create, validate, and distribute adaptive learning pathways across high-stakes training environments.
Not an 'AI quiz app'. The defensible technology is the closed loop connecting content, learners, memory, assessment, and institutional intelligence.
A domain-agnostic engine.
Our first vertical is medical education because it is complex, high-stakes, evidence-heavy, and requires continuous proof of competence. But the engine does not stop there.
Anywhere knowledge must be measured and maintained.
Future domains
EOSIA, EOSIA Health, MyQCM.
The DeepTech parent — the knowledge intelligence engine.
The vertical dedicated to medical education.
The flagship product, in the hands of Algerian students.
From professors to CTOs, into the AI era.
Along the way, we worked with respected people — from professors at my medical faculty to technical CTOs. And today, because of the AI era, it is becoming possible not just to make a neuro-symbolic system work, but to help build it.
Today I am proudly the solo founder, CEO and CTO of EOSIA — alongside freelancers and teammates pushing with me toward the big vision.

Chaib Mohamed
Founder · CEO & CTO
Medical student turned builder of a knowledge intelligence ecosystem. From a Word document to EOSIA.
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