(WO) — SLB and Qualcomm Technologies have entered into a collaboration aimed at bringing edge artificial intelligence capabilities closer to oilfield operations, enabling real-time decision-making across wells, production facilities and energy infrastructure.
Under a memorandum of understanding announced Monday, the companies will combine Qualcomm’s low-power edge computing and AI processing technologies with SLB’s Agora edge AI and Internet of Things (IoT) platform, which was developed for remote and operationally complex energy environments.
The collaboration comes as operators increasingly adopt automation and autonomous workflows across production systems, driving demand for AI applications that can operate directly at the asset level rather than relying solely on centralized computing resources.
“Together, SLB and Qualcomm Technologies aim to help operators apply AI more effectively across energy infrastructure,” said Rakesh Jaggi, president of Digital at SLB. “Many energy operations rely on real-time decision-making in remote environments where connectivity and responsiveness directly affect performance.”
According to the companies, deploying AI closer to field equipment can help improve operational responsiveness, reduce latency and support more resilient operations in environments where connectivity may be limited.
The collaboration will focus on integrating AI applications into production operations by combining SLB’s digital production technologies and energy domain expertise with Qualcomm’s edge processing capabilities.
“Many industrial environments require AI systems that can operate with limited power, constrained connectivity and real-time operational demands,” said Nakul Duggal, executive vice president and group general manager for automotive, industrial and embedded IoT and robotics at Qualcomm Technologies. “This collaboration brings Qualcomm Technologies’ low-power AI processing closer to energy operations, alongside operating assets.”
SLB said the initiative is intended to help operators modernize legacy operating environments, strengthen cybersecurity across operational technology systems and advance the adoption of autonomous workflows.
The agreement reflects a broader industry trend toward deploying AI directly within field operations as energy companies seek to improve efficiency, enhance decision-making and support increasingly autonomous production systems.
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