Data is the key input for software systems and decision-making processes.
Effective tools and engineering practices for storing, aggregating, and refining data with machine learning are essential for maximizing its value.
Data engineering solutions should be reliable, correct, and perform at scale. We apply DataOps, MLOps, and functional programming principles to make this a reality.
Articles from this team on our blog
25 May 2023
PBT and the Ghost in the Machine
Commandeering techniques from richly typed, functional languages into Python for fun and profit. In this episode: Testing strategies.
20 April 2023
Processing medical images at scale on the cloud
To allow innovation in medical imaging with AI, we need efficient and affordable ways to store and compute at scale.
4 April 2023
Python Monorepo; Part 1
How to build your Python monorepo from scratch: structure and tooling
14 March 2023
FawltyDeps is a new tool to help you identify undeclared and unused dependencies in your Python code, making your projects leaner and more reproducible.
19 January 2023
Dial M for Monoid
Commandeering techniques from richly typed, functional languages into Python for fun and profit. In this episode: Typeclasses and continuation-passing style.