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AI Customer Support Automation

3,000 Tickets a Month and Every One Waited for a Human — Even Password Resets

A PE-backed managed services operation had every ticket — from password resets to complex configurations — landing in the same queue for a human. KeyDelta deployed an AI virtual agent that autonomously resolves 55% of tickets while escalating frustrated or complex cases with full context.

55%

Auto-Resolution

Over half resolved by AI

−47%

First Response

47% faster for humans too

91%

CSAT (AI Tickets)

Matching human baseline (89%)

−34%

Support Cost

34% reduction per ticket

Full context

Escalation Quality

Sentiment + history

+42%

Agent Satisfaction

Meaningful work, not resets

The Situation

Every ticket — the same queue, the same wait.

A PE-backed managed services operation was fielding 3,000+ IT support tickets and emails per month for a flagship product. Every ticket — from password resets to complex configuration issues — landed in the same queue and waited for a human. Staffing costs were climbing, wait times were growing, and customer satisfaction was slipping as the business scaled. The team needed to handle more volume without proportionally more headcount.

3,000+ monthly tickets for a single product line — all requiring human triage and response

Simple issues (password resets, status checks, how-to questions) consuming 40%+ of agent time

Average first-response time of 4+ hours during peak periods — customers escalating out of frustration

No sentiment awareness — frustrated customers got the same queue position as routine inquiries

Support team scaling linearly with ticket volume — every 500 new tickets required another FTE

The Approach

Resolve, enrich, route — with full context.

KeyDelta built an AI virtual agent that sat at the front of the support queue — resolving what it could, enriching what it couldn't, and intelligently routing everything else:

1

Contact Suite Integration

Deployed on Evolve Contact Suite with a .NET backend. The virtual agent intercepted inbound tickets and emails natively within the existing support workflow — no new tools for customers or agents to learn.

2

Knowledge & Resolution Engine

Trained on the product's knowledge base, past ticket resolutions, and support documentation. The agent could diagnose common issues, walk customers through solutions, and execute routine actions like password resets and configuration checks autonomously.

3

Sentiment Analysis & Smart Escalation

Rolling-window sentiment analysis tracked customer tone across the full conversation trajectory — not just per-message classification. Escalation triggers fired on negative sentiment trends, multi-step complexity, and out-of-scope detection. Human agents received full context, sentiment trajectory, and a recommended resolution.

4

Voice Channel Extension

LiveKit and Broadworks integration extended the virtual agent to voice channels. Customers calling in got the same AI-first experience — with seamless handoff to human agents when needed, preserving full conversation context across channels.

The Results — 9 Months

Customers happier. Team happier. Costs down.

Auto-Resolution

0%55%

Over half resolved by AI

First Response

4.2 hrs2.2 hrs

47% faster for humans too

CSAT (AI Tickets)

N/A91%

Matching human baseline (89%)

Support Cost

$18/ticket$11.80

34% reduction per ticket

Escalation Quality

BlindEnriched

Sentiment + history

Agent Satisfaction

3.14.4 / 5

Meaningful work, not resets

Framework

Why it worked — the VOOCS lens

V

Vision

Customers get answers in minutes, not hours. Humans handle hard problems, not password resets. Support scales with software, not headcount.

O

Outcomes

Resolution rate, CSAT, and cost-per-ticket tracked per channel from day one. The AI earned its place by outperforming the baseline on customer satisfaction.

O

Ownership

Product support owned resolution accuracy. AI ops owned model performance. Escalation quality was a shared metric — both teams accountable.

C

Cadence

Daily resolution audits, weekly CSAT reviews, monthly cost analysis. Bad resolutions caught within hours and fed back into training.

S

Scale

Added a second product line in month 7 without additional infrastructure. The system handles 2x ticket volume on the same architecture.

"We were hiring a new support agent every time we added 500 customers. Now the AI handles the straightforward stuff better than we did — 91% CSAT on AI-resolved tickets, matching our best humans. Support costs dropped 34%. But here's what surprised us: agent satisfaction jumped from 3.1 to 4.4 because they stopped doing password resets and started solving real problems. Customers happier, team happier, costs down. That's the math every CEO wants to see."

— KeyDelta Advisory

Support scaling linearly with volume? Automate the routine.

An AI virtual agent with sentiment-aware escalation reduces cost and improves CSAT at the same time.

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