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About Us

We bridge the gap between technology and compassionate care.

We design human-centred systems that

  • Simplify clinical workflows
  • Improve documentation accuracy
  • Keep critical patient information securely connected

Our name

Akili means intelligence

The name is inspired by the wisdom and memory of elephants. It reflects our belief that healthcare should combine knowledge with empathy and precision.

Our platform brings together

  • AI-driven documentation
  • Patient engagement
  • Data insight tools

A connected ecosystem for modern healthcare.

Our Team

Meet the team behind Akili AI

Founded by professionals with experience in pathology, patient care and data science.

  • Charles Faul

    Founder & CEO

    Charles Faul

    Builds AI systems that augment healthcare professionals, drawing on over a decade of experience across molecular diagnostics, machine learning and public health innovation in Africa, including founding South Africa's first private BGI-powered sequencing facility.

    LinkedIn
  • Lucas Lotter

    Founder & COO

    Lucas Lotter

    Leads operations and growth at Akili AI with over nine years of experience spanning diagnostics, lab management and entrepreneurship, including co-founding Akili Labs and leading a public-private partnership to modernise Zambia's Maina Soko Medical Centre laboratory.

    LinkedIn
  • Dr Vengal Medapati

    Chief medical officer

    Dr Vengal Medapati

    Leads clinical strategy and medical governance at Akili AI as a double board-certified Plastic Surgery Consultant with over a decade of experience in aesthetic and reconstructive surgery, microsurgical techniques and patient-centred care.

    LinkedIn

Who we work with

The future of healthcare, one consultation at a time

From hospitals and clinics to research organisations, Akili AI helps professionals work more efficiently, make better-informed decisions and deliver high-quality care.

  • Hospitals
  • Clinics
  • Research organisations

From our research

Applied Machine Learning2 December 2021

Utility of a Machine-Guided Tool for Assessing Risk Behaviour Associated With Contracting HIV in South Africa

Clinical research evaluating a machine learning-based HIV risk assessment tool using structured questionnaires and validation against HIV testing outcomes in South Africa.

Read the research

Want to see what we're building?

Explore our features and discover how Akili AI supports clinical documentation, scheduling and patient management for South African practices.