Our Work


Targeting businesses with high freight expenses and vendors providing shipping quotes, EureekaBI's product allows users to estimate how much freight shipping should cost accounting for the origin and destination, time of year, and type of shipment. Enplus worked with EureekaBI to develop and validate on historical data, without lookahead bias, their model for estimating current prices and predicting future trends.


Started by Harvard University professors, Tripod is the leading source of student feedback for K-12 educators. Enplus has worked with Tripod to design, architect, and implement the backend data processing system responsible for turning raw student responses into reportable metrics. The system has been used to process responses for tens of thousands of students.


As part of prototyping the product they ultimately delivered to market, Sense needed a way to better visualize the data they were modeling. The data to be visualized was recorded every second over periods of days and weeks. Accordingly, the system needed to be able to ingest, filter, and serve large amounts of data. We designed and implemented the data visualization, data ingestion process, and RESTful backend.


As an IoT company, Flo manages large amounts of data. We designed and implemented their initial model for calibrating user devices and built out the production system, interfaced through a RESTful API, for managing the entire workflow related to user device calibration. System was designed to be cloud native with Docker containerization and the ability to horizontally scale to meet variable loads on the system.


LinkCycle, a TechStars & MIT start-up, uses data science to help large manufacturing companies dramatically reduce production costs without installing expensive sensing equipment. Enplus worked with LinkCycle to develop the underlying models for attributing and costing production costs.


Healthrageous, a digital health management company, helps individuals prevent and self-manage chronic health conditions. Enplus worked with Healthrageous to optimize the calculation of metrics used in their customer reports. As a result of our work, we reduced the calculation time by orders of magnitude, eliminated possibilities for data inconsistencies through improved database structure, and increased the usability of the system for internal business analysts responsible for supporting the product.

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