工廠僅利用8%數據，Applied Computing融資2000萬美元用AI解決
工業ai初創公司applied computing獲得由kbr領投的2000萬美元融資，推出orbital模型，結合時序、物理和llm預測設施狀態，將數周的檢查縮短至分鐘。
applied computing secured $20m in series a funding led by engineering firm kbr to expand its industrial ai model, orbital, which targets the oil and gas sector's massive data fragmentation problem. the model uniquely fuses time-series data, physics-based constraints, and large language models to predict facility states, allowing technicians to run simulations that previously took days or weeks. the company reports reaching double-digit millions in arr within 18 months and counts wipro and kbr as partners, integrating with kbr's insite 3.0 platform for ammonia production. this move pressures entrenched industrial software incumbents like aspentech and aveva by offering a specialized, physics-aware ai solution rather than generic automation.