When the oilfield meets the algorithm, transformation happens. SLB (NYSE: SLB)—the global energy technology powerhouse formerly known as Schlumberger—has launched Tela™, a next-generation agentic AI assistant designed to revolutionize how upstream energy operations are managed, automated, and optimized.
Unlike traditional automation tools that execute predefined scripts, Tela operates through a five-step agentic AI loop — observe, plan, generate, act, and learn. The result: an intelligent assistant that doesn’t just respond to data but understands objectives, makes decisions, and continuously improves its performance.
From AI Automation to Agentic Intelligence
The term “agentic AI” has quickly become one of 2025’s hottest technology frontiers. While generative AI crafts content and predictions, agentic AI systems take it a step further—acting autonomously within defined boundaries to accomplish goals.
In the energy sector, that means moving from dashboards and alerts to AI collaborators that can plan drilling steps, predict failures, and take preemptive action across wells, rigs, and production systems.
According to Rakesh Jaggi, President of Digital and Integration at SLB:
“Tela doesn’t just automate tasks — it can understand goals, make decisions, and take action. It’s the convergence of 100 years of domain science and cutting-edge digital technology, amplifying human ingenuity and redefining how work gets done.”
The impact could be enormous. With the oil and gas industry facing a shrinking workforce and rising operational complexity, Tela aims to bridge that gap—bringing AI from the control room to the wellhead.
The Tela Engine: Agentic AI Meets Energy Domain Expertise
Tela is powered by SLB’s Lumi™ data and AI platform, a system that blends large language models (LLMs) with domain foundation models (DFMs)—AI architectures specifically trained on energy-industry data and workflows.
This fusion allows Tela to interpret well logs, optimize drilling parameters, and even anticipate equipment failures before they happen. It can collaborate with engineers in real time or act autonomously to keep operations running smoothly.
Lumi’s agentic framework also gives customers the ability to build and deploy their own Tela agents, integrating partner-developed solutions or customizing capabilities for specific operational needs. This modularity echoes what’s happening across tech—where open, composable AI systems are rapidly replacing closed, siloed automation.
Why Agentic AI Matters for Energy
AI adoption in energy has historically lagged behind sectors like finance or healthcare—but that’s changing fast. The shift toward digital oilfields and intelligent infrastructure has created new pressure to unify data, automation, and decision-making under one umbrella.
Agentic AI, in this context, represents the next step: systems that see the whole operation, anticipate what’s next, and learn from every interaction.
Or as Jaggi puts it:
“The real promise of agentic AI isn’t just faster workflows—it’s the ability to see the whole system, anticipate what’s next, and act with confidence.”
For SLB, that means a smarter, more autonomous energy ecosystem—one where AI continuously optimizes exploration, drilling, and production with minimal human intervention, while maintaining full human oversight.
Cloud, Edge, or On-Site — Tela Goes Where Energy Happens
Recognizing the hybrid nature of modern energy operations, Tela is deployable across SLB’s platforms and software applications, both in the cloud and on-premises. That flexibility is crucial for clients operating in regions with strict data residency requirements or limited connectivity.
By embedding Tela directly within SLB’s existing ecosystem, the company ensures AI becomes an integral collaborator, not an add-on—a principle echoed across the growing trend of “AI inside” enterprise software.
Why It Matters
The energy industry is in the midst of a digital reinvention. As carbon targets, geopolitical shifts, and efficiency pressures converge, AI-enabled automation is no longer optional—it’s operational.
Tela represents a paradigm shift from reactive AI to proactive intelligence, and if it delivers on its promise, SLB could set a new benchmark for how AI reshapes industrial workflows far beyond oil and gas.
In a field known for its precision and risk, Tela’s arrival signals a new reality: AI isn’t just analyzing the energy industry—it’s starting to run it.
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