Every crew on the map, moving in real-time. Every task completion, photo, and issue flows back through Codex onto the manager's screen. Field learnings feed into organizational memory for the next crew.
Real-time
Crew tracking
< 5s
Issue escalation
100%
As-built coverage
Live monitoring, issue escalation, as-built capture, and organizational memory — everything that happens after dispatch.
GPS streaming from every mobile device. Live positions, task progress, and ETAs visible to the operations manager in real-time on a single map view.
Technician reports a problem with voice and photo. AI analyzes the situation against network topology and generates three courses of action. Engineer approves. Phone updates instantly.
Every step completed, every photo, every deviation from the design writes back to Codex automatically. The as-built record is a byproduct of doing the work — not a separate documentation step.
When a crew discovers a shallow conduit, that fact updates the topology, adjusts future optical budgets, and warns the next crew automatically. Every deployment makes the next one smarter.
Every crew visible on the map, moving in real-time. Every task completion, every photo taken, every AI conversation, every issue reported flows back through Codex and onto the manager's screen. When a technician hits a flooded manhole, the AI generates three reroute options in seconds. The engineer approves one, the technician's phone updates instantly, and the as-built documentation captures the deviation automatically.
GPS streaming from every mobile device. Live positions, task progress, and ETAs visible to the operations manager in real-time.
Technician reports a problem with voice and photo. AI analyzes the situation against network topology and generates three courses of action. Engineer approves. Phone updates instantly.
Every step completed, every photo, every deviation from the design writes back to Codex automatically. The as-built record is a byproduct of doing the work — not a separate documentation step.
When a crew discovers a shallow conduit, that fact doesn't just fix today's job — it updates the topology, adjusts future optical budgets, and warns the next crew automatically.
Operational Memory
Jax agents learn from your natural language instructions about your unique processes and edge cases. E.g. “reserve 20% spare fiber capacity on all feeder cables by default.”
“Reserve 20% spare fiber capacity on all feeder cables by default”
Jax.Memory
Field observations, OTDR measurements, crew performance, and anomalies flow into a persistent memory layer. Patterns crystallize into learnings that shape future network designs automatically.
Optimal splice window: early morning
327 deployments
Rocky terrain: use micro-trenching
89 deployments
Reserve 20% feeder capacity in growth zones
156 deployments
Pole route > underground where frost depth > 1.2m
43 deployments
Crew pairs outperform larger teams on drops
214 deployments
829 deployments analyzed · 5 active learnings · 94% peak confidence · Always improving.
Dispatched crews appear on the manager's real-time map. GPS streaming begins. ETAs calculate based on Mapbox routing.
Watch progress in real-time. When issues arise, the AI escalation engine generates options. Approve and push updated instructions.
As-built documentation writes itself. Field learnings feed organizational memory. The platform gets smarter with every meter of cable laid.
See how Nexma Live gives you complete visibility into every crew, every task, and every issue in the field.