An AI agent that picks up ServiceNow tickets, cross-checks Zabbix, talks to the employee in Arabic, and resolves issues before they reach an L2 engineer — with a tamper-evident audit trail.
Same job, two very different timelines. Each row pairs the L1 task with the agent's equivalent — and the real-world delta between them.
Manual handling · 8h shift · breaks needed
Autonomous · 24/7 · no breaks
Resolution time collapses from half an hour to under ten seconds — and the agent handles a thousand tickets in parallel.
Every ticket flows through the same path: ingest → verify → decide → dialog → resolve or escalate.
Agent listens to ServiceNow webhooks and pulls employee + device context from CMDB.
Cross-checks the employee's claim against live Zabbix metrics and active triggers.
Decides: matches, employee_wrong, l1_wrong, or both_wrong — with rationale.
Proposes a KB-grounded remedy in the employee's language and awaits a reply.
Closes the ticket if resolved — or escalates to L2 with all evidence packaged.
Faisal triages every ticket and routes it to the right specialist — networking, endpoint, identity, or telecom — each with a domain-specific knowledge base.
Triage agent
Network specialist
Endpoint specialist
Identity specialist
Telecom specialist
ServiceNow, Zabbix, CMDB, and email — real reads and writes, not theatrics.
Every decision in a hash-chained log — provable, signed, and replayable.
Live step trace, verifications, verdicts, and confidence at every stage.
Native Arabic dialog from day one — no MT artifacts.
Cloud Run, Kubernetes, or your own bare metal — your infra, your data.
Only the genuinely complex 10% reach a human — and they arrive packaged.
Sign in with the demo credentials and watch the agent resolve real tickets autonomously.
