A shared inbox with SLAs and a knowledge base, plus an AI that drafts a KB-grounded reply for every ticket — the repetitive ones and the tricky ones. Your team reviews and sends, so nobody starts from a blank page.
Assign, collaborate, internal notes & collision detection.
Priorities, escalation timers and rules that route to the right team.
Governed, KB-grounded drafts for every ticket — a human approves and sends.
Self-service articles you author once, that ground every AI draft.
Set the rules once. From the moment a ticket lands, it is triaged, routed and timed — so nothing waits in a shared mailbox hoping someone notices.
Priorities and escalation timers keep urgent work visible; routing rules push each ticket to the team that owns it. The shared inbox stops two people answering the same customer with collision detection, and internal notes keep the back-and-forth off the customer thread.
A built-in knowledge base turns every good resolution into a reusable answer — for your customers to self-serve, and for the AI to draft from.
Ask for a draft on any ticket, or let an opt-in background bot post one as an internal note. Every reply is draft-and-approve by default — and when you opt a queue in, the bot auto-resolves the tickets it’s confident it fully answered from your knowledge base, emailed from your own mailbox. Anything it’s unsure about stays a draft for a human.
Customer PII is masked before the model sees it — the AI works on client_4821, your agents see Henderson Ltd.
It matches the question to your published answers and best-model-per-job routing writes a reply grounded in your KB — not a guess.
On-demand, or from an opt-in per-queue bot (off by default), it posts a suggested reply for review. Turn on auto-resolve and the bot goes one step further on the high-confidence, KB-grounded answers — emailing the reply from your own mailbox and closing the ticket. Everything it’s unsure about stays a draft, and a customer reply reopens the ticket.
The agent edits and sends — the human stays in the loop on every customer-facing reply.
You can see exactly what the AI drafted and why — an auditable trail, not a black box.
The AI drafts on tokenised content, so customer PII never reaches the model. Every AI draft is logged, and every customer-facing reply waits for a human.
How SCRS works →PII masked before AI; rehydrated only for your agents.
Know exactly what the AI drafted, and why.
Sensitive replies are draft-and-approve by default.
Queues, multi-channel intake, SLAs, a customer portal, CSAT, time tracking and analytics — all sharing one dataset with your CRM and Live Chat.
Ticketing is included on Business-tier seats. Email/web intake, auto-assign, AI draft replies, auto-resolve and CSAT emails are opt-in per queue and off by default — nothing auto-emails or auto-acts on a customer until you turn it on. Built-in payments run on Revolut; nothing here is externally certified.
The same shared inbox, SLAs and governed AI — tuned to how careful, client-facing teams actually work.
Client queries about filings, invoices and documents — draft the routine answers, keep every reply draft-and-approve, and keep each ticket in the same governed dataset as your CRM.
Legal & accountancy →Patient PII is tokenised before the model and never used to train it. The AI deflects FAQs from your KB; clinicians approve anything that touches care.
Healthcare →Handle application and policy questions at volume with SLAs you can prove. Audited drafting means every AI-suggested answer is on the record.
Mortgage & IFA →Most help desks sit outside your data and pipe customer details to the model in the clear. Ours lives inside one governed suite.
| Other Me Ticketing | Bolt-on help desk | |
|---|---|---|
| PII before the AI | Tokenised first — never reaches the model | Often sent in the clear |
| AI draft trail | ✓ Every draft logged | Limited or none |
| Customer-facing replies | Draft-and-approve by default; opt-in auto-resolve | Autonomous send, always on |
| Knowledge base | Built in, grounds every AI draft | Separate tool / stale wiki |
| Links to CRM & Live Chat | One dataset, zero integrations | Integrations to wire & sync |
| Models | GPT, Claude, Gemini, Grok — best per job | Single vendor model |
Tickets flow in from Live Chat, link to the CRM record, and trigger Flows — one governed dataset, zero integrations.
