Built for SUNIST-2 experiment analysis, TokaPilot brings experimental data, analysis programs, diagnostic tools, and shared knowledge into a single entry point. Researchers use natural language to query shots, retrieve data, plot, analyze, summarize, and review anomalies.Hand repetitive data retrieval, script hunting, and figure stitching to the system—people only verify results and make physics judgments. Single-shot waveforms, discharge summaries, threshold adjustment, and anomaly detection can all be delegated to it, with results returned as plots, tables, and reports. Web and Feishu data stay in sync, so you can start an analysis anytime.

TokLabel (Tokamak Label Suite) is an open-source fusion data labeling platform co-developed by Startorus Fusion and Tsinghua University, built on the open-source Label Studio and released under the Apache 2.0 license. Fusion AI researchers spend roughly 70% of their time on data preparation, and TokLabel targets exactly this stage.It turns raw discharge data into labeled datasets ready for fusion AI. Researchers simply input a shot number to automatically retrieve data and generate labeling tasks — labeling feature moments such as breakdown, disruption, and end on one-dimensional time series, and configuration information such as the last closed flux surface on two-dimensional visible-light images. Labeling results are stored by shot number and directly consumed by downstream model training such as disruption prediction, discharge feature recognition, and configuration recognition, saving roughly 70% of data-preparation time.