The problem field operations have been waiting to solve Field operations are one of telecom's largest OPEX items and one of its most human-dependent. Every time a technician needs guidance, an authorisation, or a second opinion, the call goes to the NOC or CO - a scarce pool of experts who handle everything sequentially, across 7 to 10 systems, under pressure. The bottleneck is not the technician. It is the substrate underneath. Previous attempts at AI augmentation stayed on slides. The tools weren't fast enough, the integrations weren't deep enough, and the governance wasn't there. LIA FieldOps is the answer to all three. A three-body solution LIA is an autonomous, composable, ODA-aligned AI agent that acts as the first operational decision layer for telecom field operations. She pairs with the field engineer through every step of a service visit - from dispatch to fix and beyond. The architecture is built from 3 purpose-fit components: Tech Solutio's Pantheon-based orchestration is LIA's mind - governing decisions, enforcing confidence thresholds, and managing risk policies. Volt Active Data's VoltDB in-memory operational store is her nervous system - returning every operational read in sub-10ms, fast enough that the full detect-decide-act-audit cycle runs in real time during the visit. Binom's embeddable SDK is her hands and senses - a white-labeled mobile interface that plugs into the operator's existing field workflow without ripping it out. Every business capability is exposed via 10 TM Forum Open APIs mapped to ODA-aligned MCP servers. Any backend, any operator, same blueprint. What LIA does on a visit LIA reads the customer state, device telemetry, port topology and equipment manuals from the operator's systems in real time, and queries all of them concurrently in a single MCP session. A human NOC escalation runs those same lookups sequentially, across multiple systems. LIA collapses them into one pass. She guides the engineer step by step. When she needs data from the field, she emits a structured survey that renders as native UX elements in the mobile app, instead of a text message read in a wiring closet. Every step is captured, every decision is logged with a full audit trace, and every claim she makes is one click away from the source that produced it. LIA does not improvise. When uncertainty is high, she performs a structured handover to NOC/CO with full context, rationale, and actions taken - so the expert picks up exactly where she left off, with nothing to reconstruct. After the fix, at the moment customer goodwill peaks, she detects the trust window and surfaces a context-aware offer for the engineer to present in person. In production. Measurable. Scalable. LIA is live at Vivo (Telefónica Brazil), where she already resolves 37% of CO-escalation conversations end-to-end with no human handoff - using only 6 playbooks and limited integration. Average Handling Time dropped 40% in the first 90 days. The same architecture at full integration projects 60% autonomous resolution. New capabilities ship as playbooks, not software releases. Vivo has 27 more in the pipeline. At champion scale - TurkNet alone operates 912,500 field visits per year at €25.2M annual field-ops cost - even a 1% reduction in unnecessary truck rolls means nearly 10,000 fewer field trips. The operational and environmental impact compounds with every playbook added. Champion operators on this Catalyst include Telefónica/Vivo (Brazil), TurkNet and Omantel. LIA FieldOps is a repeatable blueprint any CSP can adopt - and a concrete, governed path to TM Forum Autonomous Networks Level 4. Field operations have been waiting for years. LIA is finally here.