Prototype demo
AI Voice Intelligence
AI can transcribe a conversation in seconds. The real value starts when it understands the conversation in context — across every conversation that came before it.
Don't just transcribe conversations. Understand them.
Demo data — fictional customer
Demo scenario
Anna Müller — Head of Operations
Step 1 — Context
Before analysing today's call, the concept loads what this customer said in previous conversations.
3 months ago
“Our SAP integration is still causing problems.”
AI memory · Recurring issue detected
6 weeks ago
“Can you make sure this gets resolved before our next review?”
AI memory · Promise detected
2 weeks ago
“We haven't seen much progress.”
AI memory · Relationship risk increasing
Today
New conversation available
Today's conversation
Quarterly operations review
We've talked about the SAP integration several times now. The problem is still affecting our operations, and honestly, I'm getting frustrated because we were told this would be resolved by now.
I understand. Let me check where we are with the technical team and make sure we get a clear update.
I really need a concrete answer this time. We can't keep discussing the same problem every few weeks.
Demo data — fictional customer
Step 5 — Scale
127
Conversations analyzed
18
Recurring issues detected
7
Unresolved product problems
4
Emerging customer risks
Conceptual demo metrics — not real customer data.
Emerging product problem
SAP integration
Detected across multiple fictional customer conversations.
Signal
Increasing
Potential action
Investigate product / technical root cause.
How does it work?
01
Voice
Customer conversation
02
Transcription
Speech → text
03
Understanding
Topics · sentiment · intent · entities
04
Memory
Previous conversations · promises · issues
05
Reasoning
Patterns · changes · relationships
06
Action
Recommendations · priorities · next steps
Differentiation
Traditional conversation intelligence
AI Voice Intelligence
Product story
Customer conversations contain some of the most valuable information inside a business. Yet much of that information disappears after the meeting.
The opportunity is not simply to transcribe conversations. It is to create a continuously evolving layer of business memory that connects what was said today with what happened yesterday — and turns that context into action.
Product management case study
Problem
Important customer intelligence gets lost in conversations.
Insight
Conversation data becomes much more valuable when combined with historical context.
Product idea
AI-powered conversation intelligence with memory.
Differentiator
Understand conversations across time, not only individual calls.
Validation
Prototype and concept development.
Next step
Validate with real users and customer discovery.
Kayky AI
The assistant answers from the same verified knowledge base used across this site.