Agentic L1/L2/L3 ticket management with intelligent triage, auto-resolution, and proactive SLA monitoring.
ArqSupport is a multi-agent platform for intelligent ticket triage, automated resolution, and proactive SLA management. It transforms manual support queues into an agent-driven resolution process that handles L1 tickets autonomously, assists L2 with context and draft resolutions, and escalates L3 cases with full context assembled. A centralized knowledge base, real-time SLA tracking, and a live analytics dashboard give operations teams full visibility into queue health.
Built for: IT operations, shared services, HR ops, finance ops, and any support team
Typically owned by: VP IT and CIO for enterprise IT support; Head of Shared Services and Director of Support Operations; Director of HR Operations; CFO and Director of Finance Operations; COO for cross-functional consolidation.
Targets we engineer each deployment toward, measured against your baseline during rollout.
High-volume support queues are processed manually by teams that spend most of their time on repetitive issues with known resolution patterns. Triage is inconsistent — routing depends on who reads the ticket. SLA monitoring is reactive, with breaches discovered after they happen. Knowledge is scattered across documentation sources and the heads of experienced team members.
ArqSupport converts a reactive manual support operation into an intelligence-driven queue where L1 issues resolve automatically, routing is consistent, and SLA breaches are prevented rather than discovered. Senior staff handle the cases that require their judgment, not the cases a well-configured knowledge base could resolve.
A reusable workflow spine, tuned to your data, systems, and controls — not a generic model wrapper.
NLP-based classification assigns every ticket to the correct tier based on content, historical patterns, and configured categories. Routing is consistent, immediate, and auditable — not dependent on who reads the ticket first.
For L1 tickets, the Resolution Agent queries SOPs, FAQs, and past cases and drafts the resolution directly. Human agents review and send rather than compose from scratch.
Tracks each ticket against its SLA continuously and escalates approaching breaches before they occur — with configurable escalation rules, priority adjustments, and notification routing.
Triage, Resolution, and SLA Monitor agents operate in concert with an Orchestrator coordinating handoffs. The architecture scales horizontally as volume grows — adding agent capacity, not headcount.
SOPs, FAQs, runbooks, and historical ticket-resolution pairs are ingested into a vector store queried in real time. The knowledge base improves as resolved tickets feed back in, and coverage gaps surface automatically.
Tracks ticket trends, category distribution, MTTR, SLA compliance, and AI confidence scores in real time — so managers spot systemic issues and retraining needs without lag.
Every agent action carries the trigger, the reasoning, the inputs, and the outcome in an encrypted, persistent audit trail. No black boxes.
The Triage Agent reads each incoming ticket and assigns tier, category, and priority from content analysis and configured rules. The Resolution Agent queries the knowledge base and either auto-resolves L1 tickets or drafts a suggested resolution for the human agent at L2.
The SLA Monitor Agent runs a continuous loop tracking time-to-breach for all open tickets. The Orchestrator routes tickets between agents and manages escalation when SLA thresholds are approached or agent confidence falls below the configured threshold.
Accelerators move fastest when the first release is narrow, measurable, and connected to the people who own the work.
Workshop to define ticket categories, SLA thresholds, and knowledge base scope; audit existing documentation for ingestion.
Knowledge base ingestion and vector store setup; configure the Triage, SLA Monitor, and Orchestrator agents.
Triage Agent and SLA Monitor go live on the existing queue, running alongside the current process to validate routing accuracy.
Resolution Agent deployed for L1 auto-resolution; analytics dashboard launched; knowledge base expanded from live gap analysis.
Auto-resolve the repetitive 20–30% of L1 categories and route the rest consistently, around the clock.
One agentic queue for HR service requests and finance ops tickets, grounded in your own SOPs and policies.
Consolidate cross-functional support queues onto one triage-and-resolution spine with per-function SLAs.
ArqSupport connects to the ticketing, communication, and knowledge systems your team already uses — ServiceNow, Jira, Zendesk, Teams, Slack — and goes live alongside the existing process before taking on autonomous resolution.
A two-week review of ticket category distribution, resolution patterns, SLA performance, and knowledge base content inventory. Delivers a categorization map showing the L1 auto-resolution opportunity and a phased deployment plan for the agent architecture.
Book itArqSupport is an agentic ticket and service management accelerator. AI agents triage every incoming ticket, auto-resolve L1 issues from your knowledge base, assist L2 with drafted resolutions, and monitor SLAs proactively — escalating before breaches occur, not after.
Typically 40–60% of L1 tickets resolve without human composition, depending on knowledge base coverage. The Resolution Agent drafts from your SOPs, FAQs, and past cases; humans review and send, or the ticket resolves autonomously once confidence thresholds are met.
No. It connects to ServiceNow, Jira Service Management, Zendesk, or Freshservice and adds the agentic triage, resolution, and SLA layer on top of the queue you already run.
IT operations, HR operations, finance operations, and shared services — any support team with high ticket volume and repetitive L1 categories. It supports cross-functional consolidation onto one agentic queue with per-function SLAs.