Customer support
Tickets resolved, not deflected.
Most support queues are the same thirty questions asked a thousand ways. This pipeline reads each ticket, identifies the customer and their order or account, finds the answer in your knowledge base and systems, and either resolves it or hands a fully prepared case to the right person. Money-moving actions wait for approval, and every answer cites its source.
- 60–70%
- Tickets resolved by agents
- < 5 min
- First response
- 0
- Refunds without approval
How it runs
Step through the pipeline.
Click a step or let it play. The ticket record on the right fills in as the agents work.
Step 01 of 08
Take in every channel
Email, chat, WhatsApp and web forms land in one queue. The agent detects the language, the customer and the intent.
- Ticket
- Email · Spanish · ‘My order arrived damaged’
- Customer
- —
- Priority
- —
- Answer
- —
- Action
- —
- Reply
- —
- Escalation
- —
- Knowledge
- —
01 · Take in every channel
Email, chat, WhatsApp and web forms land in one queue. The agent detects the language, the customer and the intent.
Tools: Zendesk / Intercom / Freshdesk, WhatsApp. Output: Ticket.
02 · Identify the customer
The customer, their account, orders, plan and past tickets are pulled so the answer is about them, not generic.
Tools: Shopify / CRM, Billing. Output: Customer.
03 · Classify and prioritise
Intent, urgency and sentiment are scored against your SLAs. Anything legal, safety-related or angry is flagged for a person immediately.
Tools: Velum agent. Output: Priority.
04 · Find the grounded answer
The agent retrieves the relevant policy, help article or runbook and checks it against the customer's situation, citing the source it used.
Tools: Knowledge base, Notion / Confluence. Output: Answer.
05 · Take the action
Standard actions such as a replacement, a tracking update or an address change are carried out in the right system. Refunds and credits above a threshold are proposed for approval.
Tools: Shopify / ERP, Stripe. Output: Action. A person approves before this step completes.
06 · Reply in their language
The reply is written in the customer's language and your brand voice, with tracking links and next steps, not a template.
Tools: Help desk. Output: Reply.
07 · Escalate with context
Cases the agent should not handle go to the right team with the customer, history, attempted answer and a suggested resolution already written.
Tools: Help desk, Slack. Output: Escalation.
08 · Close the knowledge gaps
Questions the knowledge base could not answer are clustered weekly and turned into draft articles for the support lead to approve.
Tools: Knowledge base. Output: Knowledge.
Impact
What changes when it runs.
Illustrative targets from comparable engagements. Your baseline is measured in the audit and the targets are agreed before we build.
Hours saved and ROI
What it is worth to your team.
Start from our defaults for this pipeline, then move the sliders to your numbers. The maths is simple and shown.
Based on routine tickets taking five to eight minutes each and two thirds being resolved end to end, leaving the team with complex cases and reviews.
Eight support agents each spending 30 hours a week on routine tickets at a $32 loaded hourly cost, with 60 percent resolved end to end: about 144 hours a week back, roughly $240,000 a year, while response times fall from hours to minutes.
Gross capacity, not cash savings. Excludes implementation, software and supervision costs, which are quoted before we start.
Your numbers
An assumption to explore, not a promised result.
What that is worth
144 h
reclaimed every week
$239,616
value per year
624 h
every month
3.6 FTE
of capacity returned
Hours on repetitive work, per week
Gross capacity estimate, not cash savings. Excludes implementation, software, and supervision costs. We validate assumptions in the audit.