Cut first-response time 60–80%. Ship it in 14 days.

AI support automation uses large language models to read every inbound support ticket, classify urgency and category, detect sentiment, and either draft a first response for agent review or route the ticket to the right queue with context attached. It is background infrastructure for your support team — not a customer-facing chatbot. The agent still decides what to send; the AI eliminates the repetitive typing.

Pilot Workflow: $990 USD (€900 / £790 / A$1,490), 3 days — one live support-triage automation, credited toward the Sprint if you proceed. Full Sprint: $6,500 USD fixed (€6,000 / £5,200 / A$9,800), 14 days. Monthly running costs typically $80–$200 USD depending on ticket volume (Claude API + hosting + monitoring). At a mid-market SaaS processing 2,000 tickets per month, all-in first-year cost is under $9,000 USD. Payback is usually 6–10 weeks from agent-time savings alone.

No — and projects that frame it that way fail. The AI drafts; the agent edits and sends. The headcount stays; the work shifts. Agents spend their day on tier-2 and tier-3 conversations that actually require human judgement, not typing the same password-reset reply twenty times. Response quality often goes up, not down, because agents have time to actually think.

Zendesk, Intercom, Help Scout, Freshdesk, Front, and anything with a public API. The workflow reads inbound tickets via webhook, runs classification and drafting with Claude, and writes back either a draft response (visible to the agent) or a full auto-reply (for simple tier-1 cases you explicitly opt in to auto-reply for). For uncommon or proprietary help desks, the workflow builds on top of whatever API is exposed.

In production deployments: 92–97% accuracy on category and urgency classification for SaaS support tickets, measured against 30-day review windows. Accuracy is higher on well-defined categories (billing, auth, known bugs) and lower on ambiguous cases (feature requests mixed with complaints). The workflow always includes a confidence threshold — below the threshold, tickets skip auto-routing and go to human triage. That keeps the failure mode safe.

14 days, shipped on the AI Automation Sprint. Days 1–3 discovery and design, days 4–9 build and integration, days 10–12 shadow mode (workflow drafts, agents still send — you compare output to the human baseline), day 13 cutover, day 14 handoff with documentation. Fixed price, fixed timeline, guaranteed live or refunded.