AI that resolves the tickets it can, drafts the ones it can't
BeforeQuery reads incoming tickets, answers the ones it has grounded evidence for, and drafts a reply for the agent to review on the rest — inside Zendesk, Freshdesk, Front, Intercom, Jira Service Management, Linear, and Salesforce Service Cloud. Deflection, triage, and copilot in one place.
What Support Ticket AI does
Grounded ticket answers, agent drafts, and safe deflection — measured with simulations before you enable it
Answer, don't hallucinate
Grounded Ticket Resolution
- Reads every incoming ticket and retrieves from your indexed knowledge
- Responds directly only when confidence clears the threshold
- Cites the exact source pages behind every response
- Falls back to a human agent when evidence is thin — never invents policy
- Works alongside your existing macros and automations
In-agent, one click to send
Agent Copilot Drafts
- Draft reply appears inline in Zendesk, Freshdesk, Front, Intercom, Jira SM, Linear, Salesforce
- Grounded in your knowledge base and past resolved tickets
- Insert, edit, regenerate — the agent stays in control
- Tracks which sources produced each draft, for audit
- Per-knowledge-base persona and tone applied consistently
Classify at intake
Triage & Routing
- Auto-label tickets by topic, urgency, or product area
- Route to the right queue on classifier confidence
- Skip triage for tickets the AI can resolve outright
- Trigger AI Actions (with approval rules) for common ops
- Metering separates resolved, deflected, and escalated counts
Replay before you deploy
Safe Rollout with Simulations
- Simulate the AI against your last N days of resolved tickets
- Human-review queue for every simulated response
- Per-topic accuracy scores before anything goes live
- Enable auto-response gradually — by queue, tag, or confidence tier
- Traces record retrieval + generation for every real reply
The full lifecycle, one product
Before the ticket, in the ticket, after the ticket
Support Ticket AI is deliberately end-to-end. Answer the question in the support form before a ticket is filed (form deflector). Resolve or draft when it is (helpdesk integrations and copilot). Score the outcome and route the gap into a doc proposal for your team to publish (evals + gap analytics). Every step runs on the same knowledge base and the same retrieval pipeline as the widget and bots — improve your docs once, and every surface gets better.
- Form deflection stops repeat questions from becoming tickets
- Copilot drafts land inside your helpdesk agent view
- Auto-resolution runs on confident, grounded answers only
- AI Actions (refunds, status lookups) gated by human approval
- Weak-answer traces feed doc proposals that fix the underlying gap
What teams say
Deployed in production, cited by the buyers who chose it
“Deployed on our docs site in an afternoon. Every answer has citations, and the abstention gate means we've never had a customer complain about a made-up answer.”
PN
Priya Nair
Head of Customer Support · Supabase
“The knowledge base connected to our Slack, Confluence, and helpdesk in one setup. On-call teams get the same cited answer whether they ask in chat, in the widget, or from Cursor.”
TR
Tom Richter
IT Operations Manager · Grafana Labs
“The gap analytics turned into a real docs backlog. Deflection went up because we finally knew which pages were missing — the AI told us.”
AC
Ana Castillo
VP of Customer Experience · Clerk
Frequently Asked Questions
Common questions about Support Ticket AI
Native helpdesk AIs only see the tickets and articles in that helpdesk. BeforeQuery indexes the ticket history plus your docs, wikis, code repos, connector sources, and past resolved tickets across systems — and surfaces the same knowledge base to the widget, bots, and MCP endpoint. One knowledge base, every surface, and you keep the choice of helpdesk.
Retrieval and generation both carry a confidence score. Above a threshold you set per queue, the AI can respond directly; below it, the reply is offered as a draft in the agent's helpdesk view. Simulations let you calibrate that threshold on historical tickets before enabling anything customer-facing.
Answers are generated only from retrieved chunks of your indexed content, the prompt enforces grounding in those sources, and the abstention gate blocks generation below the confidence threshold. Every drafted or auto-sent reply records its retrieved sources — you can reconstruct any answer from traces.
Both. AI Actions run under approval rules you define — sensitive invocations go through a human-approval queue, and every invocation is logged. Read-only actions (order lookup, status check) can be allow-listed to run without approval; write actions default to approval-required.
As monthly AI questions, the same unit that covers the widget, bots, and MCP. Flat pricing (Free / Pro / Enterprise) with clear included quotas — not per-ticket metering — so a busy support week never surprises your invoice.
Zendesk, Freshdesk, Front, Intercom, Jira Service Management, Linear, and Salesforce Service Cloud. Ticket history from any of them can also be indexed as a source, so past resolutions inform future answers.
Turn your ticket queue into an AI-assisted workflow
Connect your helpdesk, run a simulation on last month's tickets, and see the deflection and draft-accept rates before you enable anything customer-facing.
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