Challenge 01
The fault fires. Nobody acts.
Alert hits the NOC; someone may pick it up. Calls, parts checks, dispatch — minutes gone before anyone rolls.
AI dispatch for ATM, telecom, and medical — assignment in minutes, no coordinator.

Challenge 01
Alert hits the NOC; someone may pick it up. Calls, parts checks, dispatch — minutes gone before anyone rolls.
Challenge 02
No fault context or parts plan — diagnose from scratch, more returns, SLAs slip.
Challenge 03
Ops can't see the field in real time. Status lives in calls; escalations vanish; the SLA clock keeps ticking.
Challenge 04
Monitoring, ERP, inventory stay siloed. A human bridges them every time — that's the bottleneck.
Global dispatch
One layer: ingest → assign → parts → follow-up → close → analytics. No handoffs.
Fault in. Ticket open.
Monitoring fires (SCADA, NOC, telemetry, legacy) → ingested via API. Classified by type, asset, severity, site — no triage queue.
Best match. Seconds.
Scores crew by availability, location, certs, load. Full fault context on mobile before roll.
Parts before arrival.
Checks stock, reserves parts, coordinates delivery — crew arrives to fix, not hunt parts.
AI nags so you don't.
Tracks open tickets; pings on delays; escalations go engineer ↔ AI — fewer missed updates.
Close clean.
Confirms fix → closes ticket → CRM/reporting updates → compliance docs generated.
Live view across engineers, tickets, assets. SLA risk early; resolution and first-fix tracked automatically.
Four segments, one dispatch core.
Industry segments
Offline ATMs bleed revenue. Route alert → field without a manual queue.
Alerts, assets, crew, parts — no call-center triage.
~5 min dispatchvs ~45 min manual
Proof