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AI-CRM for a dry-cleaning network
CleanCo · 2025Voice AI · OpenAI · PostgreSQL · Twilio

AI-CRMforadry-cleaningnetwork

A CRM that calls clients, reminds, cross-sells and closes tickets on its own. Before — 3 operators. After — one operator plus an agent.

Brief

CleanCo — a 60-location dry-cleaning network. A customer drops off a coat and disappears for six months. We built an AI-CRM: a voice agent calls, a messenger reminds, a model predicts churn. Repeat orders went up 42%.

Context

Scale

60 locations, 120,000 clients in the database. 3 call-centre operators physically can't cover it.

The pain

Customers come once and disappear. Without reminders, LTV is zero past the first ticket.

Goal

Lift repeat orders 30%+ without hiring more operators. Keep a human tone.

What we did

How we built it

01

Customer base

Built a unified profile: order history, contact channel, preferences, churn prediction.

02

Voice agent

It calls, greets by name, talks about a seasonal service. The person doesn't realise it's AI.

03

Messengers

Reminders and promos go to the channel the client chose. Service, not spam.

04

Churn prediction

The model flags "fading" customers — they get the first call.

The customer journey

From first order to repeat. The agent leads the way; the operator only steps in on hard cases.

01Customer profile — history and churn prediction
02Agent call — the script adapts in real time
03Manager dashboard — share of repeat orders
Results

What came out

+42%

more repeat orders

−67%

less load on operators

60

locations under one system

4 wk

to launch

“Reviews say "thanks for the reminder". They don't realise that was an AI calling.”

Aleksey Krylov

CEO, CleanCo

Project team
IG

Igor Golikov

Lead

VK

Vitaly Kust

Tech

YK

Yuka Kust

ML

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