A helpdesk AI layer sits in front of Freshdesk, Zendesk or Intercom and does three things: classifies incoming tickets, retrieves the right knowledge base article, and drafts a reply. On the RTX 5060 Ti 16GB at our UK dedicated GPU hosting a single card handles 5,000-8,000 tickets per day with room for embeddings, reranking and an LLM draft, while keeping customer PII under your GDPR controls.
Contents
- End-to-end ticket workflow
- AI pipelines on one card
- Capacity and throughput
- Freshdesk and Zendesk integration
- Deflection metrics
Ticket workflow
- User submits a ticket via email, web form or chat widget
- Webhook fires on ticket creation and hits your middleware
- Phi-3 mini classifies intent and urgency (billing, bug, account, how-to)
- BGE-M3 retrieves top 20 KB articles, BGE reranker picks top 5
- Mistral 7B FP8 drafts a reply grounded in the retrieved snippets
- If confidence > 0.8 and intent is “how-to”, auto-reply and mark as pending customer confirmation
- Otherwise attach the draft as an internal note so the human agent edits and sends
Pipelines
| Stage | Model | Latency |
|---|---|---|
| Intent classification | Phi-3 mini FP8 | 80 ms |
| Urgency score | Phi-3 mini FP8 | 60 ms |
| KB retrieval (embed query) | BGE-M3 | 8 ms |
| Vector search + rerank | Qdrant + BGE reranker | 60 ms |
| Draft reply (RAG, 300 tokens) | Mistral 7B FP8 | 2.5 s |
| Total per ticket | ~2.8 s |
Capacity
| Daily ticket volume | Per-ticket GPU time | Fit on 5060 Ti? |
|---|---|---|
| 1,000 | ~2.8 s | Trivial (47 min of GPU/day) |
| 5,000 | ~2.8 s | Comfortable (3.9 h/day, batched) |
| 8,000 | ~2.8 s with 16-way batch | Fits within working hours |
| 15,000+ | Same | Add second card or move to 5080 |
Integrations
- Freshdesk: webhook on Ticket Created, POST to your middleware, write reply back via
/api/v2/tickets/{id}/replyor add a private note with/api/v2/tickets/{id}/notes - Zendesk: Triggers + webhooks on ticket creation, use Sunshine Conversations API for auto-reply, or Side Conversations for internal agent drafts
- Intercom: Canvas Kit app exposes AI draft in the agent side panel
- Jira Service Management: Automation rule -> webhook -> reply via
/rest/servicedeskapi/request/{id}/comment
Metrics
Well-tuned AI helpdesks deflect 20-40 percent of tickets at FAQ-level confidence and reduce mean first-reply time from hours to seconds for auto-replied tickets. Track deflection rate, auto-reply accuracy (sampled), agent time saved per ticket, and CSAT on AI-touched tickets to confirm the model is helping rather than frustrating users. See our customer support use case.
Deflect tickets with a private AI helpdesk
Blackwell 16GB for Freshdesk and Zendesk. UK dedicated hosting.
Order the RTX 5060 Ti 16GBSee also: customer support, classification, document Q&A, RAG stack install, SaaS RAG.
