石油プラントはデータの8%しか活用していない:Applied Computingが$20Mを調達しこれを解決
産業AIスタートアップのApplied ComputingはKBRが主導する$20Mの資金調達を実施し、時系列・物理・LLMを組み合わせて設備の状態を予測し、数週間かかる調査を数分に圧縮するモデル「Orbital」を立ち上げた。
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.