The caller asking “where is my refund?” gets the answer in one ring, from the ticket record, in their language — not eleven minutes of hold music and a transfer.

Conversations become tickets with the transcript, the customer record and the relevant KB article already attached — agents start at the middle, not the beginning.

Refund-dispute language, legal keywords, a platinum account, rising frustration: routed to humans immediately, by rules you write — the AI never argues with an angry customer.

“Does the education discount stack with the annual plan?” — asked by the agent in a private chat, answered from the pricing policy with the document attached, before the customer finishes the sentence.

Scheduled AI reviews read the week’s tickets for what no one agent sees: the spike after Tuesday’s release, the confusing invoice line, the KB article everyone searches for and nobody finds.

Every AI-drafted reply, macro update and trend report lands in Output awaiting review. Your team lead decides what goes out and what goes live.

KB exports, PDF policies, screenshots of error states, recorded walkthroughs — the ingestion pipeline turns the scattered knowledge into one queryable system.

The customer-facing AI and the agent assistant read the same libraries at different permission levels: update the refund policy once and both answer correctly from that moment.

If the knowledge base does not contain the answer, the AI says so — to the agent and to the customer. Guessing is not a support strategy.

Ticket-trend review, KB-gap report, escalation digest, QA sample review: work types molded to your operation, with default libraries and examples per type.

The AI’s workload is managed like the team’s: one-click views show what is urgent, late, today and tomorrow — nothing slips through shift change.

Every work is a full session: reasoning streamed, tickets cited, milestones tracked, linked to the release or the account it belongs to.

Escalation matrix, refund authority levels, SLA definitions, the incident-response playbook, the tone guide: one library, current versions on top, superseded drafts outranked.

“Can I authorize a refund over 500 without a lead?” — answered in seconds with the policy attached, while the customer is still on the line.

The AI drafting an outage notice reads from the incident playbook; the escalation digest reads from the matrix — by construction, not by memory.

New agents learn your ticket workflow, escalation rules, refund authority and tone guide through guided training — taking real tickets in days, with the assistant as a safety net.

“How do I merge duplicate tickets?” — asked to the assistant, answered from the playbook, without a hand in the air or a customer on hold.

Private chats work on any device with a login — the how-to knowledge follows the agent from the floor to the late shift to work-from-home.

Ticket arrives → classified by topic and urgency, routed to the right team, first reply drafted from the matching article — the agent opens a ticket that is already half-worked.

Sentiment drops across an account’s tickets → the team lead gets an alert with the history summarized and cited — the save call happens before the cancellation email.

Resolution → the follow-up goes out in the customer’s language, on your schedule; detractor responses open a review ticket automatically.

Detractors from last quarter, accounts with three-plus escalations, customers affected by Tuesday’s incident: audiences built from your own support history — no list ever exported.

The apology note and the survey read naturally in the customer’s own language — your support voice, their words.

Opt-outs and contact preferences are enforced by the system, not by memory. Every send is on the record.

Tickets, customers and articles mapped field by field, with a dry-run preview before anything writes — push, pull or two-way, your choice per object.

Salesforce and HubSpot connectors sync accounts and contacts push, pull or two-way — support and sales finally read the same customer story.

A full API for whatever else the floor runs: the billing system, the status page, the QA tool — data in, results out, under scoped keys.

The server redacts what a role cannot see — a tier-1 agent sees the ticket, not the account’s billing history; an outsourced agent sees even less, by your design.

A searchable log of every audited action: who read which transcript, who changed the refund policy, who exported which report, and when.

Five-level workgroups map teams, tiers and sites; the on-premises option puts transcripts, knowledge and customer records physically inside your building.

Ask the chat: “where is my refund?” — watch it answer from records, stay claim-guarded, and escalate gracefully when you push past its knowledge.

Ask: “how would you draft a reply to an angry billing ticket?” — it walks the workflow it would run in your tenant, grounded, cited, agent-reviewed.

The full demo loads a support tenant with sample tickets: routing, trend reviews, draft replies, CSAT flows — your queue, working.