Find and compare
Ask which stores changed, how orders compare or what a relevant operating manual says.
AI ANALYSIS
Ask what changed. Check the evidence.
Ask questions across connected sales and operating records. Review the source, the interpretation and the next check instead of receiving an unexplained answer.
Currently serving operations in South Korea. International rollout and PoC inquiries are welcome.
A useful answer starts with the right data.
DX connects the records. Business concepts and their relationships add context. AI helps you explore the evidence and decide what to check next.
Understand the limits
An answer should identify missing inputs and distinguish an observed change from a possible explanation.
Decide the next check
Use the recommendation to investigate. A generated answer does not mean an action has already been executed.
Try an operating question.
Interactive examples explain the workflow. They are not customer performance claims.
ASK · CHECK · DECIDE
Start with a question about your business.
Why did sales fall at Daehakro?
- Evidence
- Example data: KRW 1,100,000, compared with KRW 2,450,000 on the same weekday last week.
- Interpretation
- Sales fell by approximately 55%. This comparison identifies a change, but does not establish its cause.
- Next check
- Compare channel-level order counts, average order value and trading hours before deciding what to change.
Scripted illustration, not a live AI response. No action is executed. Available answers depend on connected data and access permissions.
Connected records give your questions context.
Start with DX: align the store, business date and menu behind each record. Then use the connections to investigate your operating questions.
- 01 · CONNECT
Sales and operations
POS, QSC, staffing and visitor counts, within the agreed integration scope.
- 02 · ADD CONTEXT
Concepts and relationships
Define how stores, menus, staff and operating records relate. Retrieve relevant data and approved documents.
- 03 · ASK & CHECK
Evidence before action
Ask AI, review the source and its limits, and choose the next check.
Ontology defines concepts and relationships; graph models represent relationships; vector search supports retrieval. These are complementary techniques, not interchangeable claims.
Questions before you start
What can I ask?
You can ask about connected data and approved documents: sales comparisons, purchasing relative to sales, QSC differences or operating instructions. Coverage depends on connected sources and permissions.
What happens when the data is missing?
The answer should identify the missing inputs and propose what to check or connect. It should not invent an exact metric from incomplete records.
What do ontology, graph and vector search mean here?
An ontology defines business concepts and relationships; a graph represents relationships; vector search helps retrieve relevant information. They support data context and retrieval, with the implementation depending on the agreed scope.
START A CONVERSATION
Tell us about your operation.
Discuss a Korea rollout or share your interest in an international deployment or PoC. We will review systems, data and the scope with you.
01
Consultation
Workflows and store count
02
Tailored demo
Data and feature scope
03
Plan a pilot
Timing, fees and rollout criteria