Independent Team-Matching Initiative | ATF AI Challenge Phase 2 · Health

Africa’s Intelligence. One Collective Mission.

Africa has the talent. Africa has the challenges. Bringing complementary minds together is where meaningful collaboration begins.

AFRIQON — African Intelligence Quotient — is an independent, participant-led coordination initiative created to help interested individuals explore potential team formation around the Health Sector track of the ATF AI Challenge, Phase 2.

We aim to connect people across AI, software development, healthcare, biomedical sciences, research, data, product innovation and other relevant disciplines. The objective is simple: identify complementary capabilities and create opportunities for purposeful collaboration.

This is an internal team-matching invitation, not an official ATF launch event, recruitment exercise or announcement. Participation in AFRIQON does not replace any official ATF registration or eligibility process.

Apply to join our team Explore the selection process
  • Five members per team
  • Merit-based candidate assessment
  • Multidisciplinary collaboration
  • Pan-African representation
AFRIQON Sovereign Neural Grid
Pan-African Regional Telemetry
Multi-Region Active

Intelligence is greater when it works together.

The future of artificial intelligence in Africa will not be determined by technology alone. It will be shaped by the people who understand Africa’s problems, the communities affected by them, and the possibilities of applying intelligent systems to address them.

The best teams are not necessarily made up of the five strongest individual applicants. They are made up of five people whose capabilities complement one another.

A technically gifted developer may build a functional application, but a health professional can help ensure that the solution addresses a genuine clinical or public health need. A researcher strengthens the evidence base, while a product thinker translates ideas into usable, scalable instruments. AFRIQON harmonises these pillars.

Our institutional objectives

  1. Identify capable, highly committed participants from the ATF AI School Phase 1 community.
  2. Architect balanced, multidisciplinary teams combining technical execution and clinical/domain expertise.
  3. Encourage structural gender, nationality, and institutional diversity across squads.
  4. Match individuals intelligently based on demonstrated competencies, background metrics, and project goals.
  5. Establish an elite collaborative environment for developing practical AI-driven healthcare solutions.

Health: Exploring AI for better health outcomes.

The focus of this AFRIQON team-matching initiative is the Health Sector track of the ATF AI Challenge Phase 2. Across African health systems, complex challenges persist regarding access to care, disease surveillance, diagnostics, resource allocation, and evidence-informed health policy decisions.

Artificial intelligence offers opportunities to improve how these challenges are understood and addressed. AFRIQON seeks to connect people with complementary capabilities who are interested in exploring these opportunities collaboratively.

Important Clarification

AFRIQON is not defining the official ATF problem statement, technical requirements or challenge rules. Participants should consult official ATF communications for authoritative information. Any potential team collaboration must align with applicable ATF guidelines and requirements.

We are looking for builders interested in deploying AI toward:

  • Disease prevention, predictive surveillance, and outbreak intelligence
  • Healthcare accessibility, triage, and decentralized service delivery
  • Health data intelligence platforms and clinical decision support systems
  • Biomedical research, clinical data synthesis, and evidence generation
  • Digital health architectures and health information management systems
  • Public health and clinical workflow optimization
  • Community health education, behavioral engagement, and localized outreach
  • Responsible, ethical, and inclusive AI applications in low-resource environments

Different minds. Complementary capabilities. Shared purpose.

AFRIQON welcomes expressions of interest from individuals with diverse academic, technical, research and professional backgrounds who are interested in exploring collaboration around AI and health. You do not need to be a core software engineer to contribute meaningfully to a multidisciplinary team.

AI & software development

Engineers who build, integrate, test, and deploy AI models, automation workflows, and robust software architectures.

Data science & analytics

Specialists skilled in exploratory data analysis, Python/R, statistical modeling, machine learning, and telemetry visualization.

Health & biomedical sciences

Medical doctors, public health practitioners, pharmacists, nurses, laboratory scientists, and clinical researchers.

Research & evidence

Experts in study design, systematic reviews, data synthesis, evaluation frameworks, and scientific documentation.

Product & innovation

Thinkers who map user needs, design intuitive product workflows, guide business model viability, and manage milestones.

Communication & community

Communicators who synthesize complex technical narratives, coordinate stakeholder alignment, and drive adoption.

During the expression-of-interest process, participants can indicate their primary area of expertise, additional skills, interests and availability. This information will help inform potential team-matching discussions.

A transparent selection process built on merit and balance.

Each team consists of exactly five members. AFRIQON employs a rigorous multi-tier evaluation system to guarantee equitable, highly functional team distributions.

  1. 1

    Apply

    Complete the application portal detailing your professional background, geographic region, technical proficiencies, core track preferences, and portfolio links or evidence of past work.

  2. 2

    Assessment

    Submissions are systematically graded across a comprehensive framework measuring technical capability, health domain knowledge, product orientation, and execution reliability.

  3. 3

    Intelligent team matching

    Qualified candidates are mapped into potential 5-person cohorts designed to maximize skill coverage, sector expertise, product strategy, and geographical diversity.

  4. 4

    Expert review & approval

    Algorithmic squad formulations undergo qualitative review by committee leadership to confirm operational synergy before final sign-off.

  5. 5

    Notification

    All candidates receive outcome updates. Approved members gain immediate access to their assigned team workspaces, resources, and onboarding instructions.

Individual merit. Collective strength.

The AFRIQON matching index weighs individual excellence heavily while balancing vital macro-team composition metrics.

Individual Assessment Breakdown (85 Total Points)
Evaluation Pillar Max Points
Technical capability & execution25
Health domain expertise & context20
Product thinking & innovation mindset15
Commitment, availability & reliability15
Communication & teamwork aptitude10
Total Individual Weight85 pts

Our Equity Guarantee

We do not treat raw programming speed as the sole indicator of impact potential. Gender balance, geographical representation, and diverse institutional backgrounds operate as essential structural criteria. Sensitive details beyond functional selection criteria are never required, and all final placements receive human committee verification.

Team composition parameters (15 points)

Team-level scoring variables guarantee that assembled squads operate with zero blind spots:

  • Complementary division of technical and non-technical proficiencies
  • Comprehensive AI pipeline build and integration coverage
  • Embedded public health and medical domain expertise
  • Active research, synthesis, and evidence validation skills
  • Balanced gender and demographic representation
  • Multi-country representation and regional collaboration
  • Institutional and professional background variety
  • Synchronized availability for sprint deliverables

Have something valuable to contribute?

If you are interested in exploring collaboration with people from complementary disciplines around the Health Sector track of the ATF AI Challenge Phase 2, AFRIQON invites you to express your interest. This form is exclusively for AFRIQON’s internal team-matching and coordination exercise. It is not official ATF registration, does not guarantee team placement and does not confer eligibility to participate in the challenge. Please consult official ATF communications for authoritative information about eligibility, registration, rules and deadlines.

Apply to join our team
AFRIQON — AFRICAN INTELLIGENCE QUOTIENT ✦ AFRICA'S INTELLIGENCE. ONE COLLECTIVE MISSION. ✦ INDEPENDENT PARTICIPANT-LED TEAM-MATCHING INITIATIVE ✦ OUR VISION: AFRICAN INTELLIGENCE SHAPING HEALTHIER COMMUNITIES AND THE FUTURE OF GLOBAL AI ✦ AI · HEALTH · RESEARCH · DATA · PRODUCT · INNOVATION ✦ ATF AI CHALLENGE 2026 · PHASE 2 · HEALTH SECTOR ✦ CONNECTING DEVELOPERS · HEALTH PROFESSIONALS · RESEARCHERS · DATA SCIENTISTS · PRODUCT THINKERS ✦ COMPLEMENTARY SKILLS. SHARED INTELLIGENCE. AFRICAN-LED INNOVATION. ✦ FROM COLLABORATIVE IDEAS TO PRACTICAL, RESPONSIBLE AI SOLUTIONS FOR HEALTH ✦ QUESTIONS, ENQUIRIES OR COLLABORATION? CONTACT DANIEL ONIMISI [email protected] ✦