Have an impact

Join our team and help fix healthcare.

Our machine learning and large language models and backend systems improve the most costly and time-consuming human tasks in healthcare operations. And our customers rely on us to be correct every time. The invisible plumbing of healthcare is extremely complex, but it has an immense impact on human health, and we’re automating it bit by bit. Hospitals across the country run our code in production every day. And this is just the beginning.

Our team

machine learning

Machine learning

Productizing R&D to learn complex tasks from human experts.


Core platform

Building the platform that can be used to automate any task on a computer.



Delivering full-service automation solutions for our clients.

AKASA is enabling human health

We are the leading developer of AI for healthcare operations.

AKASA scales human intelligence with leading-edge AI and ML securely trained on customer data to learn unique systems, continuously adapt to changing environments, and deliver comprehensive automation and analytics for complex workflows. The result is a seamlessly integrated, customized solution that reduces operating costs, frees up staff to do the work they love, and helps health systems allocate resources to where they matter most.


AKASA is hiring

The engineering team embraces a work-from-anywhere attitude, where everyone is welcome.

Engineering talent at AKASA

Working at AKASA offers me a profound sense of purpose and fulfillment. I find immense satisfaction in knowing that our innovations directly contribute to enhancing the overall patient care experience. I’ve grown immensely as an engineer. I’m constantly presented with opportunities to expand my technical expertise and problem-solving skills. The collaborative atmosphere here at AKASA has been instrumental in my development; working with and learning from other talented and hard-working engineers offers me invaluable insights and new perspectives.

Aalique Grahame   Software Engineer

Engineering videos

Published Research

employee using pen to touch folders on screens

Pushing the Limits of Medical Codes Prediction from Clinical Notes by Machines

Accepted to MLHC 2021


Payer Response Prediction from Claims Date With Deep Learning

Accepted to ICML2020