工厂仅利用8%数据，Applied Computing融资2000万美元用AI解决
工业ai初创公司applied computing获得由kbr领投的2000万美元融资，推出orbital模型，结合时序、物理和llm预测设施状态，将数周的检查缩短至分钟。
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.