PROPOSALwith-mcp

Automating customer support with AI

A proposal for faster, more consistent answers

Prepared for Acme Corp.

November 2026

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Chapter 1with-mcp

Where support stands today

What is actually happening in the inbox

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Current challengeswith-mcp
  1. 70% of tickets repeat the same questions
  2. Average time to first answer is 2 business days
  3. Quality depends on who happens to pick up the ticket
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Our approachwith-mcp

01

Instant answers to FAQs

AI learns from past replies and answers on the spot

02

Hand-off to people

Only complex cases reach a human agent

03

Measure and improve

Collect ratings and review them every month

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Expected impactwith-mcp

Tickets answered automatically

70%

Time to first answer

Instant

Tickets per agent

3.2x

MetricTodayAfter
Time to first answer2 business daysInstant for routine questions
Handling time per ticket12 min2 min (review the AI draft)
ConsistencyVaries by agentSame question, same answer

Sample: fictional company and figures

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Rollout in three stepswith-mcp

STEP 1

Organize past tickets

  • Collect one year of tickets and replies
  • Group them by topic

STEP 2

Pilot

  • Run in one department for two months
  • Verify answer accuracy

STEP 3

Roll out company-wide

  • Extend to every department
  • Train agents on the new flow
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Ticket volumewith-mcp

Tickets grow 20% a year and reach 1,800 a month in 2026

Routine (automatable)Complex (human)05001,0001,5002,000(tickets / month)2023202420252026 (est.)6203801,0007804201,2009404801,4201,2605401,800

How to read it

  • Growth comes from routine questions, 70% of the total
  • Complex tickets grow only 10% a year
  • Automating the routine frees agents for the complex
2026 estimate1,800 / month
Routine share70%
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Next stepswith-mcp

Let’s start with the numbers

This week

Share one year of ticket data with us

In two weeks

We return an estimate of automation rate and savings

Thank you for your consideration

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