We are building software that empowers teams to gain insight from their data. TelemetryJet was born out of a frustration: Collecting and sharing data on small engineering teams involves manual work that distracts from the core goal of using that data. TelemetryJet provides a no-code platform for data collection, analysis, and sharing, allowing your team to focus on utilizing your data to reach your objectives.
Our aim is to innovate in three areas:
Data Collection: Empower teams to easily collect data from their systems, no code required. Provide integrations for popular platforms, and powerful APIs that make it easy to connect custom data sources. Seamlessly combine data from multiple data sources into a consistent time-series database.
Data Analysis: Provide powerful tools to visualize and analyze data. Promote the creation of visualizations that are accurate, easy to interpret, and beautiful. Maintain performance even when analyzing large datasets, through intelligent streaming and filtering of data.
Data Sharing: Enable collaboration by building sharing into the platform: Teams should be able to share their data, visualizations, and dashboards instantly with anyone. Allow easy export of data from the TelemetryJet platform into standard formats when more advanced analysis is needed.
At the core of our ecosystem are the TelemetryJet CLI and TelemetryJet Arduino SDK projects. These tools empower engineers to easily monitor and control hardware, collect data points, and transmit data between sources. Both projects are completely open-source and MIT licensed: Teams are free to modify or self-host the tools as needed. We accept contributions and feature requests on our public GitHub repositories.
We also provide the proprietary TelemetryJet Cloud platform, a cloud-based UI for organizing and analyzing data that you collect from the TelemetryJet CLI or from any other hardware system. The cloud platform builds upon our open-source tools to provide a managed solution for data collection and analysis, and sharing.
The concept for TelemetryJet was influenced by our team’s work on the University of Rochester solar boat racing team. Our solar boat team took a data-first design approach which involved collecting extensive data on the performance of the boat, quantitatively analyzing the performance of drivetrain systems.
As we collected data, we recognized a core issue: Analyzing, visualizing, and sharing our data involved a large amount of manual work that distracted from our goals. Time that our team could have spent utilizing the insights to improve our systems was instead spent processing data – And sharing between collaborators was a similarly technical process.
TelemetryJet is the solution: A seamless, no-code approach to data analysis with sharing built into the platform from the start.
Chris Dalke is a full-stack software developer, maker, and an alumnus of the University of Rochester.
He's built a number of data collection systems - At UR, he was president of an electric boat racing team that competed in the Solar Splash electric boat competition. During his tenure, the team built out a telemetry and sensor system that guided driver decisions during races.
Nate Conroy is a Syracuse, NY native and an alumnus of the University of Rochester, where he graduated with a Bachelor of Science in Computer Science and a concentration in Human-Computer Interaction.
Nate's an experienced full-stack developer who has worked at Amazon and Lockheed Martin building data-rich systems.
If you have any questions or are in need of support, please contact us at firstname.lastname@example.org