Startups Using Python in Boston
Via their job posts and information submitted by startups themselves, these are the Boston Python startups we've found.
Interested in other technologies? Browse or search all of the built-in-boston tech stacks we've curated.
Tech Stack Highlights
NodeJS – Our cloud-based Microservices are primarily written in NodeJS. NodeJS allows us to develop scalable and easily deployable software for our business logic and high level robot behaviors.
ROS – Our robots run on the ROS with customizations to greatly improve performance and reliability. With LIDAR, 3D depth cameras, odometry and other sensors our robots are able to move autonomously in our customer’s facilities.
OpenCV – With 256 CUDA cores on our robot you will have access to more than a teraflop of compute on our robot. Some of our highest performance algorithms utilize OpenCV to take advantage of these parallel cores.
Angular – Our graphical interfaces are built as Angular applications running on Electron giving us ease of development running on multiple platforms and fully extensible as we design new features.
Affordable high-resolution 3D printers.
Tech Stack Highlights
C++ – The majority of our codebase (Desktop & Embedded) is written in C++. This allows us to share code across platforms, and to be able to carefully control sensitive areas of code (performance and memory-wise).
Qt / QML – We use the Qt libraries throughout our code. This allows us to extend C++ with nice features for integrating various logic areas (signals / slots), as well as a tight integration with QML, which we use for our user interface code. QML is a great way to track state transitions, both on our embedded & desktop applications. Qt also makes cross-platform code easier to develop & maintain.
Yocto – Our printer runs a custom Linux distribution, which we build using the Yocto project. This system allows us to track our firmware builds & releases in a deterministic way.
Git – All of our source code is tracked in git, which provides all of our version control needs. It works nicely with Yocto to be able to exactly specify versions of firmware builds at the package level. It also allows for good collaboration between developers while preserving the cleanliness of shipping source code.
Supply chain analytics for in-transit inventory.
Using computer vision & machine learning to turn human or animal body language into structured data, helping to develop better drugs for diseases like ALS, Parkinson’s, and Alzheimer’s.