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Growing credit accounts depended on one person joining every step together.

A full-time employee identified suitable customers, built relationships through repeated conversations, offered credit facilities, gathered application details, completed credit checks, created approved accounts and manually logged the communication history.

Bespoke SystemSee how work like this is priced ↗
TIME RETURNED8+ hrs

returned every working day

Result from this project, not a promise for every business.
BEFORE · 8+ hrs of work required every working day

Work passed from task to task.

  1. Find suitable customers
  2. Build the relationship
  3. Complete credit checks
  4. Create accounts and log contact
AFTER WEEKFOUND

One controlled AI sales agent now progresses the complete relationship.

  1. Prioritise suitable customers
  2. Prepare personalised outreach
  3. Run governed credit checks
  4. Create approved accounts and log contact

An AI sales agent turns customer relationships into approved credit accounts.

The agent uses current customer and conversation history to recommend the next action, prepare relevant messages, collect application information and call credit-check APIs. Approved accounts are added to the system and every interaction is recorded, with policy decisions and exceptions kept under human control.

  1. 01

    Joined customer records and communication history into one live relationship view

  2. 02

    Added AI recommendations and personalised message preparation for each next action

  3. 03

    Integrated credit-check APIs with business rules and human approval controls

  4. 04

    Created approved accounts in the core system and logged every interaction automatically

A full-time workload was covered—and the credit-account channel grew.

More than eight staff hours were returned every day, covering the workload of a full-time employee who had left the business. Credit-account uptake increased by 40%, approvals became 80% faster and sales in that area increased by 30%.

Figures relate to this project. We would estimate your opportunity from your own process and volumes.
About this example

This is a genuine project for a business whose identity and internal data are not published. The step-by-step illustration explains the process; it is not a screenshot or a live demo of the client’s systems.

Published by WeekFound Ltd. WeekFound was founded by Jake Lawton after more than ten years working across finance, operations and process improvement. Read Jake’s background.

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Other familiar problems.

Sales operationsQuote follow-up depended on spreadsheets and individual memory.Finance operationsFinance work was split across reports, inboxes and debtor lists.