SUPPORTIQ — Customer Support Intelligence

Total Agents

6

3 extraction · 3 decision

Tests Passing

12 / 12

100% pass rate

Avg Sentiment

Negative

Based on last 5 tickets

Escalation Rate

40%

2 of 5 tickets escalated

Agent Confidence Scores

TicketAnalyzer

—

NeedExtractor

—

SentimentAnalyzer

—

TaskPrioritizer

—

OwnerAssigner

—

EscalationDecider

—

Recent Ticket Analysis

Ticket	Customer	Sentiment	Priority	Status
#TK-89012	DataFlow Analytics	Angry	P0	Escalated
#TK-89008	TechStart Inc.	Frustrated	P1	In Progress
#TK-89004	Acme Corp	Neutral	P2	Resolved
#TK-88997	GlobalRetail	Satisfied	P2	Resolved

Customer Needs Extracted

ID	Customer Need	Urgency	Assigned To	SLA
NE-001	Resolve API 503 errors in production	CRITICAL	SRE Team	Breached
NE-002	Provide detailed post-mortem report	HIGH	Engineering	At Risk
NE-003	Discuss SLA credit compensation	HIGH	Account Mgmt	On Track
NE-004	Direct access to VP of Engineering	MEDIUM	Leadership	Pending

🎧 What is SUPPORTIQ?

SUPPORTIQ (Customer Support Intelligence) is a multi-agent system that transforms raw support tickets into actionable intelligence. It automatically analyzes customer issues, detects sentiment and frustration levels, identifies churn risk, extracts specific customer needs, and escalates critical tickets based on SLA policies and customer tier.

⚡ How It Works

Submit a support ticket with customer tier info. SUPPORTIQ runs 6 agents in sequence:

Step 1 — Extraction

💬 TicketAnalyzer

Parses the ticket content to identify the issue type, affected services, customer context, and communication tone. Creates a structured representation of the support request.

Step 2 — Extraction

🔍 NeedExtractor

Identifies specific customer needs and requirements — technical fixes, refunds, feature requests, account changes. Maps each need to resolution paths.

Step 3 — Extraction

📈 SentimentAnalyzer

Gauges customer sentiment (positive, neutral, negative), frustration level, and churn risk. Detects escalation language like threats to cancel or competitor mentions.

Step 4 — Decision

📊 TaskPrioritizer

Assigns priority (P0–P3) based on customer tier, sentiment, SLA status, revenue impact, and issue severity. Enterprise SLA breaches get P0.

Step 5 — Decision

👤 OwnerAssigner

Routes the ticket to the right team — SRE for outages, billing for charges, product for feature requests, account management for churn risks.

Step 6 — Decision

🚨 EscalationDecider

Triggers escalation for SLA breaches, high-value customer complaints, negative sentiment spikes, and tickets mentioning legal action or cancellation.

🎬 Live Agent Pipeline Demo

Watch how SUPPORTIQ processes a support ticket through all 6 agents in real-time

Subject: Production database connection timeouts
Priority: HIGH Customer: Acme Corp (Enterprise)
Body: Our application has been experiencing intermittent database timeouts since 3 AM. Multiple teams are affected. This is our third ticket this week about the same issue. We are considering switching vendors if this isn't resolved today.

🏷

Step 1

TicketAnalyzer

Idle

Category: Infrastructure · Severity: High

🔍

Step 2

NeedExtractor

Idle

DB fix needed · Recurring issue · Urgent

💬

Step 3

SentimentAnalyzer

Idle

Sentiment: Frustrated · Churn risk: High

📈

Step 4

TaskPrioritizer

Idle

P0: Critical · SLA breach risk

👤

Step 5

OwnerAssigner

Idle

DBA Team → Fix · CSM → Relationship

🚨

Step 6

EscalationDecider

Idle

⚠ Churn risk → VP escalation

✅ Pipeline Complete — 6 agents processed in 3.5s

3

Needs Found

High

Churn Risk

2

Assigned

1

Escalations

🎯 Real-World Use Cases

Enterprise Ticket Triage

Automatically classify and route thousands of daily support tickets to the right teams with correct priority levels — no manual triage needed.

Churn Risk Detection

Identify at-risk customers before they leave — detect frustration patterns, repeated issues, and cancellation signals across ticket history.

SLA Violation Prevention

Monitor response and resolution times in real-time. Auto-escalate tickets approaching SLA breach thresholds before violations occur.

Customer Sentiment Trends

Aggregate sentiment data across all tickets to identify product areas causing frustration, track CSAT trends, and measure support quality over time.

🏗 Architecture

🔄

Orchestration Engine

Coordinates all 6 agents sequentially, managing ticket state and passing analysis between each processing step.

🛡

Circuit Breaker Recovery

Per-agent fault isolation ensures a sentiment analysis failure doesn't block ticket routing or escalation decisions.

📋

Full Audit Trail

Every sentiment score, priority assignment, and escalation decision is logged — essential for SLA compliance evidence.

🎧 Submit Support Ticket for Analysis LIVE AGENTS

📄

Drag & drop a ticket file, or click to browse

.txt · .md supported

Subject Customer tier

✦ The ticket is analyzed by 6 AI agents: sentiment detection, need extraction, prioritization, routing, and escalation.

Live Agent Results

Extracted Customer Needs

Need	Urgency	Category

— or analyze a sample ticket —

📄

Ticket
Analyzer

Extraction

Idle

›

🔎

Need
Extractor

Extraction

Idle

›

💬

Sentiment
Analyzer

Extraction

Idle

›

📈

Task
Prioritizer

Decision

Idle

›

👤

Owner
Assigner

Decision

Idle

›

🚨

Escalation
Decider

Decision

Idle

Analysis Log

Submit a ticket to begin analysis…

Customer Needs

—

Sentiment

—

Analysis Time

—

Total Tests

12

Passed

12

Failed

0

Duration

1.94s

Agent Tests

TestTicketAnalyzer

test_basic_analysis0.22sPASS

test_empty_ticket0.07sPASS

TestNeedExtractor

test_need_extraction0.18sPASS

TestSentimentAnalyzer

test_sentiment0.14sPASS

TestTaskPrioritizer

test_prioritization0.12sPASS

TestOwnerAssigner

test_assignment0.15sPASS

Infrastructure Tests

TestRecoveryStrategies

test_retry_strategy0.05sPASS

test_recovery_manager0.06sPASS

TestCircuitBreaker

test_circuit_closed0.04sPASS

test_circuit_opens0.03sPASS

TestAuditLogger

test_log_event0.08sPASS

test_audit_export0.11sPASS

Total Events

22

Tickets Analyzed

5

Avg Confidence

81%

Escalations

2

Analysis Audit Timeline

14:23:01 · workflow

Ticket Analysis Started

#TK-89012 — DataFlow Analytics (Enterprise)

14:23:02 · agent

TicketAnalyzer → Complete

API outage detected · 3 failing endpoints identified

14:23:02 · sentiment

Sentiment: NEGATIVE (Angry/Frustrated)

Churn risk keywords detected: "evaluating competitors"

14:23:03 · priority

Priority Assigned: P0 — Critical

Enterprise tier + production outage + SLA breach

14:23:04 · escalation

Escalated to VP Engineering + Account Manager

Enterprise customer threatens churn · SLA violation

14:23:05 · workflow

Analysis Complete

4 needs extracted · 2 escalations triggered

Sentiment Breakdown

Customer Emotion Distribution

😠 Negative 60%😐 Neutral 25%😊 Positive 15%

🚨 Churn Risk Indicators

• "evaluating competitors" — direct churn threat
• "third outage this quarter" — pattern frustration
• "$50k/month" — high-value customer at risk
• Demands VP-level engagement

⚡ Recommended Actions

• Immediate executive outreach
• Proactive SLA credit offer
• Dedicated incident liaison
• Post-resolution QBR meeting

Circuit Breakers

6

All closed

Recoveries

2

Retry Rate

100%

Uptime

99.9%

Circuit Breaker Status

TicketAnalyzer

CLOSED

0 failures

NeedExtractor

CLOSED

0 failures

SentimentAnalyzer

CLOSED

0 failures

TaskPrioritizer

CLOSED

0 failures

OwnerAssigner

CLOSED

0 failures

EscalationDecider

CLOSED

0 failures