Gen2B AI Customer Operations
01 / Cover
AI Communication Platform

AI That Resolves Work, Not Just Conversations.

AI chat, voice, QA, and workflow automation for contact centers that need fewer manual steps.

Gen2Chat Gen2Call Gen2Agent Action Layer
17 sec first response 75% avg AI resolution 82.5% peak 67% actual payments
Kazakhtelecom Samruk-Kazyna KCell Punto Pago BI Group Kaspi
Replace with hero collage
Gen2Chat + Gen2Call + Gen2Agent + Triggers
Chat
Calls
Voice
Actions
Gen2B AI Customer Operations
02 / Pain
Same headcount. More channels. More blame.
Buyer pain

The real pain is not volume. It is manual work hiding inside every conversation.

Customers wait
First response slows.
SLA slips.
Operators repeat
Same question.
Same handoff.
Supervisors guess
QA samples.
Not reality.
Leaders overpay
More volume.
More people.
If the next step still needs a human, you do not have automation.
Gen2B AI Customer Operations
03 / Contrast
The category mistake

Most AI support tools answer. Your team still does the work.

Answers
Then stops.
  • Drafts a reply
  • Suggests a tag
  • Leaves the next step to a human
Resolves
Then moves the workflow.
  • Detects the event
  • Triggers the action
  • Stores the outcome for learning
Classify → Route → Trigger → Resolve
Better wording is not the win. Fewer manual steps is.
Gen2B AI Customer Operations
04 / Platform
One platform

One stack for the whole contact center.

One context. One action layer. One place to automate.

Gen2Chat AI inbox
Gen2Call 100% call QA
Action Layer Classify • Trigger • Execute
Gen2Agent Voice AI
Soft Collection Recovery flows
Classifiers Triggers Webhooks CRM / RPA Talk to your data
Reads the conversation. Detects the event. Triggers the action.
Gen2B AI Customer Operations
05 / Gen2Chat
Gen2Chat

Automate L1 without making support feel robotic.

Handle repetitive chat instantly. Escalate only when it actually matters.

24/7 answers
Routine chat handled instantly
Grounded replies
Answers from your business knowledge
Human handoff
Rules decide when AI steps aside
Omnichannel
WhatsApp, widget, in-app
75% avg AI resolution 82.5% peak
Replace with: Gen2Chat unified inbox
AI reply
Intent tag
Transfer to agent
Gen2B AI Customer Operations
06 / QueSMART
QueSMART

One missed chat should not punish the whole queue.

Queue logic that protects SLA without supervisor babysitting.

⏸
Missed chat
Auto-pause the rep instantly
🔄
Redistribute
Chat moves to next available
🧠
Smart routing
Skills + load + priority
⭐
Lead detected
Route to top rep
📊
Live state
Queue health at a glance
99% routing accuracy
Missed chats stop spreading when the queue can think for itself.
Gen2B AI Customer Operations
07 / Triggers
Classifiers + Triggers

If AI sees the signal, the workflow should already be moving.

Signals become actions. Not dashboards.

App issue
→ ticket + alert
Promo interest
→ sales route
VIP detected
→ priority queue
Payment risk
→ webhook / callback
Up to 10 conditions Webhooks CRM RPA
Replace with: Classifier + Trigger builder
Event detected
Rule matched
Action fired
Gen2B AI Customer Operations
08 / Self-Learning
Self-Learning Agent

Every closed conversation trains the next one.

Not static KB maintenance. A self-learning loop built from real resolved conversations.

💬
Chat closes
Conversation ends with resolution
→
🔍
AI extracts
Finds the winning answer pattern
→
✅
Optional review
Approve or auto-accept
→
⚡
Next chat resolves
Faster, with less human effort
Learns
From real operator answers
Improves
Future resolution rate
Keeps control
Human approval when needed
Resolved conversations become future automation.
Gen2B AI Customer Operations
10 / QA
Fair QA

Customer ratings punish operators for company problems.

AI scores against your checklist. Not the customer's mood.

😤
1–5 ★
Customer mood score
  • Reflects frustration, not agent effort
  • Penalizes reps for system issues
  • Inconsistent across customers
  • Drives burnout and churn
Bad rating → Lower KPI → Burnout
vs
✅
AI QA
Behavior-based checklist
  • Scores against your actual checklist
  • Consistent across every conversation
  • Separates agent skill from customer mood
  • Coaches instead of punishing
Checklist → Fair score → Growth
Score the behavior. Not the frustration.
Gen2B AI Customer Operations
09 / Gen2Call
Replace with: Gen2Call analytics dashboard
Transcript
Scorecard
Full-call QA
Gen2Call

Stop scoring 2% of calls and calling it quality.

Every call becomes searchable, scoreable, and coachable.

100% calls
No blind spots
Script checks
Policy + compliance
Semantic intent
Meaning, not keywords
Emotion
Tone + content
100% call analysis
Gen2B AI Customer Operations
11 / Gen2Agent
Gen2Agent

Not a prerecorded tree. A real voice agent.

Low-latency voice that can answer, use tools, call back, and continue in WhatsApp.

Old voice bots
Recorded. Rigid. Painful to update.
Gen2Agent
<1 sec. Tool-aware. Context-aware.
<1 sec latency Inbound + outbound Callback WhatsApp during call
Replace with: Gen2Agent live console
Live transcript
Tool usage
Callback ready
Gen2B AI Customer Operations
12 / Cross-channel
Recovery flow

No answer? Move the conversation. Don't lose it.

When voice fails, Gen2B shifts the conversation to the next best channel automatically.

📞
No answer
Call goes unanswered or drops
💬
WhatsApp sent
Automatic channel switch
🤖
AI continues
Context stays intact
✅
Resolved
Human joins only if needed
Overflow to chat
When queues spike, shift channels
Outbound recovery
Context preserved across channels
Smart callback
Schedule when timing is better
63% outbound pickup rate
The conversation moves. The context stays.
Gen2B AI Customer Operations
13 / Soft Collection
Soft Collection

When payment follow-up matters, context wins.

Recovery works better when the system remembers the customer, the promise, and the next step.

Context kept
No cold restarts
Payment links
Sent instantly
Partial pay
Handled in flow
Smart callback
When timing is better
67% actual payments rate
Replace with: Soft collection / payment link flow
Reminder logic
Payment link
Payment outcome
Gen2B AI Customer Operations
14 / Trust
SaaS VPC On-Prem
Customer-owned data
Model R&D STT / TTS
Deploy where enterprise says yes
Trust + Deployment

Built by a team that trains models — not just prompts them.

Move fast. Keep control. Deploy the way your enterprise can actually approve.

Model R&D inside
Real AI depth, not wrapper-only depth
STT / TTS inside
Voice quality and latency matter
SaaS / VPC / On-Prem
Choose the deployment path
Customer-owned data
Restricted access when required
NVIDIA KPMG HPE Elcore Group
Gen2B AI Customer Operations
15 / Proof
Production proof

This is what relief looks like in production.

First operator response
52s → 17s
-67%
Operator time per session
45m 40s → 21m 10s
-54%
Response SLA
8m 44s → 3m 18s
-62%
Avg AI resolution
75%
Live production average
Peak AI resolution
82.5%
Peak achieved
Lead conversion uplift
+15%
Gen2Chat use case
Actual payments rate
67%
Soft collection
Outbound pickup rate
63%
Production outbound
BI Group — 12h → 24/7 with the same team
Bank deployment — 99% routing accuracy
Public references — Kazakhtelecom, KCell, Punto Pago
Kazakhtelecom Samruk-Kazyna KCell Punto Pago BI Group Kaspi
Gen2B AI Customer Operations
16 / Close
Closing

The contact center does not need more tools. It needs fewer manual steps.

Start with Gen2Chat. Expand into QA, voice, and workflow execution when the buyer already feels the relief.

Start with Gen2Chat Expand to calls + voice Keep one action layer
Same team. More resolved.
Gen2Chat Gen2Call Gen2Agent Soft Collection
Replace with final ecosystem collage
One AI system
Fewer manual steps