Hi, we are mimilabs
Let's Create Your High-quality Beautiful Small Projects, One by One
"Great things are not done by impulse, but by a series of small things brought together" - Vincent van Gogh
Working in healthcare for over a decade, we have seen many small projects3 scrapped because nobody has time to work on them (or will pay for them). However, such projects could have helped many patients, providers, and administrators; they just couldn't find immediate utilities in our system.
Ironically, in our view, our healthcare system needs those beautiful small projects more than anything. They may not seem fancy, lucrative, and innovative, yet they require careful and time-consuming work. Since these projects offer limited short-term gains, there is no incentive to work on them. Nevertheless, if built well, they can have a large long-term impact. That's our starting point.
At mimilabs.ai1,2, we are working on projects that nobody has time to work on,
e.g., cataloging and analyzing publicly available datasets, solutions around extreme weather events
, underserved communities
, small practices and ACOs
, and healthcare policies
.
With our minimalistic yet high-quality engineering, we can make them widely available, beautiful, and meaningful to everybody.
We are a mission-driven company focused on long-term wins. Our projects share the common mission of helping patients, providers, and many other stakeholders in the industry. Together, by accumulating these beautiful small things, we will achieve big and sustainable industry changes.
Footnotes
1: The name "mimi" comes from the Korean pronunciation of two Chinese letters, 美微, which represent "beautiful" and "small," respectively.
2: The sound "mimi" refers to the ear (耳) in Japanese. We want to listen to small voices.
3: When we say "small projects," we mean projects a single highly skilled engineer can perform. With the advancement of AI and modularized build-ups, such small projects can have beautiful impacts. We plan to build stepping stones to moonshots.
Resources
Data Engineering
Learn about how we downloaded and ingested thousands of public datasets into our data lakehouse.