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AmexSoft.

Customer support

AI Customer Support

Handles common support intents with grounded answers, escalation paths and ticket summaries for human agents.

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AI Customer Support

Customer support

Overview

What this solution explores

This demo solution illustrates a support agent that answers from approved knowledge, opens tickets when needed, and hands off with context — instead of improvising when confidence is low.

Business problem

Where work gets stuck today

Agents spend hours answering the same status and how-to questions while complex cases wait. Knowledge is scattered and handoffs lose context.

Existing process

How the work usually moves now

  1. 01

    Customer writes to support email or chat

  2. 02

    Agent searches docs, past tickets and tribal notes

  3. 03

    Repeats the same answer with uneven quality

  4. 04

    Escalation happens late, often without a clean summary

Proposed AI workflow

The intended operating path

  1. 01Classify intent and retrieve grounded knowledge snippets
  2. 02Answer when confidence and policy allow
  3. 03Create or update a ticket for unresolved cases
  4. 04Escalate with a summary, customer goal and attempted steps
  5. 05Log citations and tool calls for review

System architecture

Building blocks of the system

Channel adapters (email, chat, helpdesk widget)
Intent classifier + retrieval over approved articles
Policy guardrails (what may be answered vs must escalate)
Helpdesk API for tickets and macros
QA sampling loop for answer quality

Integrations

Systems this design connects to

  • Helpdesk / ticketing system
  • Knowledge base / help center
  • CRM for account context when permitted
  • Identity for authenticated customer sessions

Implementation approach

How we would pilot and harden it

Cover the top intents first — not the whole catalog
Require citations or structured sources for auto-answers
Design escalation as success, not failure
Review sample conversations weekly with support leads

Potential business impact

Qualitative outcomes to validate on a pilot

These are directional benefits — not invented percentages, hours saved or testimonials.

Faster resolution for repetitive, well-documented intents
Cleaner handoffs with summaries for human agents
More consistent answers across channels
Track containment and CSAT on a pilot — do not invent metrics

Visuals

Architecture and UI slots

Reserved slots for diagrams and mocks. Empty by design until assets are produced.

Support flow

Slot for intent → answer/escalate → ticket diagram

Handoff card

Slot for agent summary card shown to human operators

Related services

Delivery capabilities behind this solution

AI Agents for BusinessAI Integration

Insights

Related insights

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