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The next evolution of Ciena’s DCOM: OOB management for diverse data center needs
2027 Intelligence Programs

LLM

LLM customization enables businesses to adapt large language models to their industry, workflows, and proprietary data. By leveraging fine-tuning, retrieval-augmented generation (RAG), and domain-specific knowledge, organizations can improve AI accuracy, automate complex processes, enhance customer experiences, and build secure, scalable AI solutions aligned with their business objectives.
AI agents rely on five core components: perception, learning, reasoning, action, and communication. This guide explains how each component works, how memory, planning, and tool use fit into modern agent architectures, and how these capabilities are applied across industries. See how your own company compares across the broader telecom AI agent ecosystem — vendors, OSS/BSS providers, system integrators, and operators.
New enterprise research shows most AI agents fail with total confidence rather than visible doubt - and that automated testing is not catching it before deployment. For operators running AI agents alongside private networks in manufacturing, mining, ports, airports and utilities, that combination changes how agent-based tools should be evaluated and rolled out.
May 2026's roundup: the US government's 10% equity stake in Intel (now valued above $50B) underscores how strategic chip manufacturing has become, India and Vietnam both advance new chip fab and testing capacity, the AI chip supply chain keeps fragmenting beyond Nvidia, and Pixxel and Sarvam AI plan India's first orbital data center satellite.
2027 Intelligence Programs
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TELECOM AI AGENTS Q3 2026 · Available Now

Explore the Telecom AI Agents Leadership Landscapes

Explore market positioning, deployment momentum and operator validation across the telecom AI agent ecosystem.

Explore Leadership Landscapes
Independent · Evidence-based · Telecom-focused