In the aviation industry, safety and reliability are paramount. Reliable Robotics, a Mountain View-based company founded in 2017 by experienced aerospace engineers Robert Rose and Juerg Frefel, is taking a measured, practical approach to enhancing aviation safety through automation. Their mission is to bring safe, certified autonomous systems to commercial and defense aviation.
The Vision: Safer, More Accessible Air Transportation
Reliable's autonomous flight system will make air travel safer, more accessible, and more affordable. Their technology, which enables remote operation across various aircraft types, has the potential to expand air transportation options and democratize access to the skies.
This vision is already taking shape. Reliable has secured key validations: their certification plan has been accepted by the Federal Aviation Administration, they're collaborating with NASA and commercial partners, and they've landed contracts with the U.S. Air Force. These achievements aren't just milestones; they are concrete steps toward proving the safety and versatility of autonomous aviation.
As they developed complex autonomous systems, Reliable recognized the need for a sophisticated platform to handle the vast amounts of information generated.
The Scalability Challenge: Harnessing the Data Deluge
At its core, Reliable is an engineering company, and engineering thrives on data. As they developed complex autonomous systems, Reliable recognized the need for a sophisticated platform to handle the vast amounts of information generated. They sought a solution that could not only manage data but transform it into actionable insights, focusing on two key principles:
- Velocity: In engineering, speed of decision-making is crucial. Reliable needed a platform that could rapidly process and analyze large, complex datasets, bridging the gap between data acquisition and informed action. This meant finding tools that could automate analysis and quickly surface key insights.
- Ubiquity: Data is most valuable when it's accessible. Reliable aimed to better democratize data across the organization, allowing any engineer to easily visualize and analyze information from vehicle, lab, and simulation telemetry. The goal was to make product data immediately accessible to any engineer, without any programming or setup.
These needs led Reliable to Sift, a unified observability platform designed for complex data environments. Sift's streaming and visualization capabilities aligned with Reliable's requirements, prompting a trial collaboration that would put the platform to the test in the demanding world of autonomous aviation.
Putting Sift to the Test
Reliable's trial period with Sift was designed to validate critical technical requirements: supporting existing analysis workflows, enhancing live streaming operations, and facilitating collaborative visualization. The stakes were high, and the platform needed to prove its mettle in Reliable's demanding environment.
The value of Sift became apparent almost immediately. This early win underscored the potential of Sift's real-time anomaly detection and collaborative analysis capabilities.
The trial involved integrating Sift into Reliable's vehicle and bench test systems. This integration yielded the following benefits:
- Real-time Accessibility: Through a combination of live telemetry streaming and post-hoc uploads from onboard systems, Sift made stripchart views and logs instantly available to the entire engineering team via web browsers.
- Enhanced Collaboration: After ingesting large volumes of data, these views could be easily shared and annotated, allowing engineers to efficiently propagate insights across the organization.
- Automated Assessment: Sift enabled the team to codify review criteria directly into the platform, facilitating automatic, real-time assessment. This feature has the potential to expedite anomaly detection and will allow engineers to quickly dive into root cause investigations.
The value of Sift became apparent almost immediately. During the very first flight with Sift deployed, the platform provided valuable diagnostic insights for the engineering team. This early win underscored the potential of Sift's real-time anomaly detection and collaborative analysis capabilities.
The Future: Accelerating Autonomous Aviation
Following the successful trial, Reliable transitioned into a full implementation with Sift. This integration will enable high-velocity, data-driven decision-making that's crucial to Reliable's mission. Reliable plans to leverage Sift's telemetry management solutions across all their simulation, test, and flight assets, streamlining data into a unified system for comprehensive analysis and review.
Sift allows engineering teams to focus more of their energy on their core mission — in Reliable's case, improving aviation safety with certified autonomous flight systems.
For complex engineering projects like those at Reliable, the ability to quickly analyze and act on vast amounts of data can be a significant accelerator. Sift's observability platform is designed to meet this need, providing tools that help innovative companies transform raw data into actionable insights. By simplifying data management and analysis, Sift allows engineering teams to focus more of their energy on their core mission — in Reliable's case, improving aviation safety with certified autonomous flight systems.
As the field of autonomous systems continues to evolve, the role of robust data management and analysis tools will only grow in importance. Platforms like Sift are poised to play a crucial supporting role, helping companies like Reliable make critical decisions more efficiently and effectively.
