Organizations in the region are encountering challenges scaling AI agent deployments. Initial experimentation often results in a proliferation of isolated agent proofs of concept, frequently accompanied by a lack of consistent operational infrastructure. This pattern is now prevalent across industries including energy, telecom, and finance. The most common response is investment in a central agent platform, consolidating fragmented agents and establishing a shared layer of functionality.
Several organizations are realizing returns from agents focused on regulated workflows. A significant portion are deploying agents for tasks such as claims processing, invoice validation, and security operations. These agents are automating previously manual processes, reducing case completion times from hours to minutes. This is particularly important given the increasing regulatory scrutiny and operational demands of these sectors.
To address the bottleneck of engineering resources, companies are enabling non-technical users to configure and deploy agents through low-code platforms. This approach allows central teams to manage standards and ensure production readiness, while still empowering business units to rapidly iterate on agent solutions. This federated building model leverages tools like LangSmith Fleet for configuration and evaluation.
Observability, evaluation, and cost control are becoming critical components of agent infrastructure. Teams are implementing centralized monitoring solutions to track agent performance, manage prompts, and control token usage. The increasing use of LLM gateways provides unified visibility across agents, models, and spend, enabling proactive governance and cost optimization. Schneider Electric, Vodafone, and monday.com are demonstrating these patterns in practice, establishing robust agent platforms to support their respective deployments.
Schneider Electric’s internal AI Hub of 350 experts supports over 60 agents across critical infrastructure, utilizing LLMOps for observability and deployment. Vodafone employs LangGraph and LangSmith for Insight Engine and Enigma, while monday.com rebuilt Sidekick into a layered system with bounded tools and sandboxes. These examples highlight the shift towards platform-based agent management.
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