Cross-database customer investigation

The challenge

A complete picture of one customer requires three systems and three people, so it is usually assembled badly or not at all.

The scenario

An account manager preparing for a renewal wants to know what actually happened with this customer over twelve months: usage, invoices, incidents and support volume, in one place.

What goes in

Billing

Invoices and payment history.

Product events

Usage events in a document store.

Support

Ticket history and resolution times.

What you can ask

Illustrative prompts. Results depend on your own data and are not deterministic.

• “Give me a twelve-month picture of this account.”Copy
• “Did usage fall before or after the support incidents?”Copy
• “Which invoices covered the period of the outage?”Copy

How Clearception approaches it

How the work is structured. Each step shows what its output is grounded in.

1. 1

   Identify the customer

   AI-inferred

   Resolve the same customer across systems that identify them differently.

2. 2

   Gather each dimension

   Source

   Retrieve billing, usage and support histories independently.

3. 3

   Align on time

   Observed

   Put the three histories on one timeline so sequence is visible.

4. 4

   Report with sources

   Observed

   Present the picture with the rows behind each element.

What you get

The shape of what comes back — not a promised result.

• Unified account timeline

  Observed

  Usage, invoices and incidents on one axis, each entry linked to its source rows.

Why it matters

One picture, not three

Sequence becomes visible, which is usually the whole question.

No export step

Nothing is copied into a spreadsheet that then goes stale.