"Sydney, Australia-based Alloy thinks it can help with that issue: the startup is building data infrastructure for robotics companies to help them process and organize all the data their robots collect from various sources, including sensors and cameras. At its core, Alloy encodes and labels the data it collects, and allows users to search through their data using natural language to find bugs and errors."
""The current pattern is, you look for some kind of anomaly, and then you'll replay the data," Joe Harris, the founder and CEO of Alloy, told TechCrunch. "They then are spending hours scrubbing through this data, looking for these issues that have been flagged to them, trying to diagnose from that [while] not really having a good view as to whether this has happened before, if it's a high-severity issue or this one-off, edge case.""
Robotics systems generate vast volumes of sensor and camera data, with even simple robots producing up to a terabyte per day. Alloy builds data infrastructure to help robotics companies process, encode, label and organize multimodal robot data. The platform enables natural-language search to find bugs and errors and supports rules that catch and flag future issues, similar to software observability tools. Alloy aims to reduce hours spent replaying and manually scrubbing data to diagnose anomalies and determine recurrence or severity. Founder Joe Harris began Alloy in 2024 after working in Australian tech and identifying data management as a persistent robotics pain point.
Read at TechCrunch
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