How Zendesk AI, Fin by Intercom, and Teravictus Work Together: The Complete Support Stack
When Air Canada's chatbot hallucinated a bereavement policy that didn't exist, the company paid $812 in damages. When McDonald's ended its IBM AI drive-through partnership after viral order failures, it wasn't because AI can't automate-it's because no one was monitoring when automation failed.
The question isn't whether to automate support. It's how to catch the critical issues that automation misses before they become churn.
Three Layers, Three Different Tools
Modern support teams need coverage across three distinct layers:
| Layer | What It Handles | Best Tool | Purpose |
|---|---|---|---|
| L0: Self-Service | FAQs, order status, simple lookups | Zendesk AI, Fin by Intercom | Deflect simple queries, 24/7 availability |
| L1: Simple Inquiries | Password resets, basic troubleshooting | Zendesk AI, Fin by Intercom | Handle straightforward requests |
| L2: Complex Issues | Billing disputes, technical problems, escalations | Human agents + Teravictus | Solve problems requiring judgment/empathy |
The Problem with L0/L1 Automation Alone
Gartner research shows chatbots achieve:
- ✅ 58% resolution for simple issues (returns/cancellations)
- ❌ 17% resolution for complex issues (billing disputes)
ASAPP found: 21% of "contained" conversations had no actual resolution-they were deflected but customers received no help.
The gap:
When L0/L1 automation fails, customers either:
- Give up in frustration (96% of churning customers never complain)
- Submit a ticket that looks "normal" but contains critical urgency
- Experience mounting frustration across multiple failed attempts
This is where Teravictus fits in.
The Complete Stack: Automation + Intelligence
Zendesk AI / Fin by Intercom: L0 & L1 Automation
What they do well:
- Deflect 50-65% of simple, repetitive queries
- Provide 24/7 self-service for basic issues
- Reduce load on human agents for routine requests
- Answer FAQs instantly from knowledge base
What they struggle with:
- Complex issues requiring judgment
- Emotional/complaint contexts
- Detecting when a "resolved" ticket wasn't actually resolved
- Identifying churn risk signals in ticket content
- Escalating critical issues before customer gives up
Teravictus: L0/L1 Quality Monitoring + L2 Intelligence
What it does:
- Monitors chatbot quality: Detects when L0/L1 automation is failing
- Catches false positives: Identifies tickets marked "resolved" but customers still frustrated
- Escalates critical issues: Real-time Slack alerts for high-urgency tickets that need human attention
- Predicts churn risk: 92% accuracy identifying at-risk customers based on ticket content/sentiment
- Assists L2 agents: Provides context, urgency scores, and churn risk to human agents handling complex issues
The key difference:
Teravictus doesn't replace your chatbot-it ensures humans intervene when chatbots aren't enough.
Side-by-Side Comparison
| Dimension | Zendesk AI | Fin by Intercom | Teravictus |
|---|---|---|---|
| Primary Purpose | Automate L0/L1 queries | Automate L0/L1 queries | Monitor automation quality + assist L2 |
| Customer Interface | Chatbot widget | Intercom Messenger bot | Human agents (AI invisible) |
| Integration | Native Zendesk only | Works with Zendesk, Salesforce, Intercom | Zendesk + Slack |
| Best For | Simple, repetitive FAQs | Self-service at scale | Complex issues requiring human judgment |
| Deployment Time | 4-12 weeks | Under 1 hour (claimed) | 10 minutes |
| Setup Complexity | High: intent mapping, training | Medium: train on help center | Low: OAuth connections only |
| Churn Prediction | Requires Explore add-on | Not included | Built-in, 92% accuracy |
| Critical Incident Detection | Rule-based, manual config | AI intent detection | AI analyzes sentiment/urgency/context |
| Monitors Bot Quality | No (only tracks containment metrics) | No (only tracks resolution rate) | Yes (detects false positives) |
| Base Pricing | Per-agent + AI usage fees | $0.99/resolution + seat costs | Usage-based per ticket |
| Minimum Spend | Varies by plan | $49.50/month (50 resolutions) | None-pay for actual usage |
| Works With Other Tools | Standalone only | Standalone or with Intercom | Works WITH Zendesk AI/Fin |
How They Work Together: The Ideal Stack
Step 1: L0/L1 Automation (Zendesk AI or Fin)
Customer asks simple question → Chatbot resolves instantly
✅ Works great for:
- • "What's my order status?"
- • "What are your store hours?"
- • "How do I reset my password?"
Step 2: Teravictus Monitors Quality
For every ticket (bot-handled or human-handled):
- • Analyzes sentiment, urgency, complexity
- • Detects churn risk signals
- • Identifies false positives (marked "resolved" but customer still frustrated)
Step 3: Teravictus Escalates L2 Issues
When AI detects critical issues:
- • Real-time Slack alert to human agents
- • Context provided: Customer history, urgency score, churn risk
- • Human intervention before customer churns
The Result:
- ✅ Chatbots handle 50-65% of simple queries
- ✅ Humans focus on high-value, complex issues
- ✅ No critical tickets slip through the cracks
- ✅ Churn prevented through early escalation
Implementation: Build the Complete Stack
Phase 1: Deploy L0/L1 Automation (If You Haven't Already)
Option A: Zendesk AI
- Timeline: 4-12 weeks
- Best for: Teams deeply embedded in Zendesk ecosystem
- Setup: Intent mapping, answer library, training
- Cost: Per-agent + AI usage fees
Option B: Fin by Intercom
- Timeline: Under 1 hour (claimed)
- Best for: Teams already using Intercom or needing multi-platform
- Setup: Train on help center, configure tone
- Cost: $0.99/resolution (minimum $49.50/month)
Phase 2: Add Teravictus for L0/L1 Monitoring + L2 Assistance
- Timeline: 10 minutes
- Setup:
- Connect Zendesk (OAuth, 5 min)
- Connect Slack workspace (OAuth, 5 min)
- Done-starts monitoring immediately
- What it monitors: ALL tickets (bot-handled and human-handled)
- Cost: Usage-based per ticket processed
Pricing: What the Complete Stack Actually Costs
Automation-Only Approach (Just Zendesk AI or Fin)
- Zendesk AI: ~$2,500-5,000+/month for 10-agent team
- Fin by Intercom: ~$1,980/month for 2,000 resolutions + seat costs
The Hidden Cost:
- • 21% false positive rate (ASAPP research)
- • No churn prediction
- • Critical issues slip through unnoticed
- • 96% of churning customers never complain
Complete Stack (Automation + Intelligence)
Chatbot (your choice) + Teravictus monitoring
What you gain:
- • Same L0/L1 deflection rates
- • + Churn risk detection (92% accuracy)
- • + Critical incident escalation
- • + L0/L1 quality monitoring
- • + L2 agent assistance with context
Teravictus Cost: Usage-based per ticket, no minimums, no seat fees
When You Need Each Tool
You need L0/L1 automation (Zendesk AI / Fin) if:
- ✅ You receive repetitive, simple queries at high volume
- ✅ You need 24/7 self-service availability
- ✅ You want to deflect routine requests from human agents
- ✅ Your FAQs are well-documented and unchanging
You need Teravictus if:
- ✅ You already use chatbots but worry about what they miss
- ✅ Churn prevention is critical to your business
- ✅ You handle complex issues requiring human judgment
- ✅ You want to identify at-risk customers before they cancel
- ✅ You need humans to focus on high-value tickets
- ✅ You use Slack for team communication
You need BOTH if:
- ✅ You want efficient L0/L1 automation AND intelligent L2 escalation
- ✅ You can't afford critical issues falling through the cracks
- ✅ You measure success by customer retention, not just deflection rates
The Data: Why Automation Alone Isn't Enough
Research from Marketing Science: When customers learn they're talking to a bot, purchase intent drops 79.7%.
Gartner Survey (5,728 consumers):
- • 64% prefer companies didn't use AI for support
- • 53% would switch to competitors if they discovered AI usage
- • Only 17% resolution rate for complex issues like billing disputes
ASAPP Research: 21% of "contained" conversations had no actual resolution-deflected but not helped.
The Silent Churn Problem: 96% of churning customers don't complain-they simply leave.
Call Center Studio: 67% of churn is preventable with first-contact resolution.
What This Means:
Your chatbot might show 60% deflection rate, but:
- • 21% of those are false positives (no actual resolution)
- • Customers who hit those false positives have elevated churn risk
- • 96% won't complain-they'll just leave
- • You won't see it in your dashboards
This is the gap Teravictus fills.
Real-World Example: The Complete Stack in Action
Scenario: Billing Dispute
9:00 AM: Customer tries Zendesk AI chatbot
- • Bot provides FAQ link about billing
- • Customer closes chat (counted as "resolution")
- • Teravictus detects: High frustration in language, billing-related keywords, churn risk score: 87%
- • Slack alert sent: "High churn risk - billing dispute - needs human attention"
9:05 AM: Human agent receives Slack alert with:
- • Customer history
- • Previous bot interaction
- • Urgency score
- • Churn risk explanation
9:10 AM: Agent proactively reaches out
- • Resolves billing issue
- • Customer retention saved
Without Teravictus:
- • Bot marks ticket "resolved"
- • Customer remains frustrated
- • No human sees the issue
- • Customer churns 30 days later
- • Shows up in metrics as "successfully deflected"
Legal Reality: Why Monitoring Matters
Case: Moffatt v. Air Canada (2024 BCCRT 149)
What Happened: Chatbot told customer he could apply for bereavement fare after travel. Actual policy: must apply before travel.
Result: $812 judgment. Company fully liable for AI misinformation.
The Lesson: You're responsible for what your chatbot says. If it hallucinates policy, you pay.
How Teravictus helps:
Monitors for policy inconsistencies and escalates questionable responses for human review before they become legal liabilities.
Bottom Line: Automation + Intelligence = Complete Coverage
Zendesk AI and Fin are excellent at what they do: deflecting simple, repetitive queries at scale.
But they can't:
- • Detect when they've failed
- • Identify churn risk in ticket content
- • Recognize critical urgency requiring immediate human attention
- • Provide context to L2 agents handling complex escalations
That's Teravictus's role.
The Complete Modern Support Stack
Layer 0/1: Automation
- Tool: Zendesk AI or Fin by Intercom
- Purpose: Deflect simple queries (50-65%)
- Customer sees: Chatbot
Layer 2: Intelligence + Human Intervention
- Tool: Teravictus
- Purpose: Monitor quality, detect churn risk, escalate critical issues
- Customer sees: Empowered human agents
The Result:
⚡
Efficiency of automation
🛡️
Safety net of human intelligence
📈
Churn prevention through early intervention
Ready to Build the Complete Stack?
If you already have Zendesk AI or Fin: Add Teravictus in 10 minutes to monitor quality and assist with L2.
If you don't have automation yet: Consider whether you need it. If you handle <100 tickets/day, Teravictus alone may be sufficient.
If you're evaluating chatbots: Plan for the complete stack from day one-automation handles volume, Teravictus ensures quality.
Research Sources:
Luo, X., Tong, S., Fang, Z., & Qu, Z. (2019)
"Frontiers: Machines vs. Humans: The Impact of Artificial Intelligence Chatbot Disclosure on Customer Purchases"
Marketing Science, Vol. 38(6), pp. 937-947
https://pubsonline.informs.org/doi/10.1287/mksc.2019.1192Gartner (June 2023)
"Gartner Survey Reveals Only 8% of Customers Used a Chatbot During their Most Recent Customer Service Interaction"
View ReportGartner (July 2024)
"Gartner Survey Finds 64% of Customers Would Prefer That Companies Didn't Use AI For Customer Service"
Survey of 5,728 consumers, December 2023
View ReportASAPP Research
"The Danger of Only Using Containment Rate to Measure Success"
https://www.asapp.com/blog/the-danger-of-only-using-containment-rate-to-measure-successMoffatt v. Air Canada, 2024 BCCRT 149
British Columbia Civil Resolution Tribunal, February 14, 2024
Read Full DecisionSuperOffice & Industry Research
"Customer Churn: 12 Ways to Reduce Churn and Keep More Customers" (citing Forum Corporation and thinkJar research)
https://www.superoffice.com/blog/reduce-customer-churn/Additional sources: Intercom product documentation, Zendesk product specifications, vendor-provided pricing and implementation timelines (current as of November 2025).
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