How Cityfurnish runs rentals end to end on an AI workforce

One of India's largest furniture and appliance rental platforms runs customer operations on an AI workforce that does the work across every channel and every lifecycle stage: inbound support on chat and social, outbound voice, and proactive outreach that listens for lifecycle events and acts before the customer asks, from signup to day-300 recovery.

275,000+

lifecycle touchpoints handled in 30 days

Every channel

chat, social, email, and voice, one workforce

Every stage

signup and KYC to renewals and day-300 recovery

The brand

Cityfurnish rents furniture, appliances, and fitness equipment on monthly subscriptions across India's major cities. A rental is not a transaction, it is a relationship with a lifecycle: signup and KYC, delivery and installation, monthly invoices, tenure extensions, ownership transfers, and eventually a pickup. Every one of those stages produces conversations, and half of them need Cityfurnish to reach out first instead of waiting for the customer to ask.

The challenge

A subscription rental business runs on operational conversations that ecommerce never sees. New signups stall at KYC. Payments fail at checkout and take a saved cart with them. Deliveries need scheduling calls, and then rescheduling calls. Invoices raise questions every month, and a missed one starts an overdue clock that can run for three hundred days. Renewals, buybacks, and ownership transfers each carry their own paperwork and their own follow-ups. The inbound queue was only half the job. The other half was outreach the team had to place manually, call by call and reminder by reminder, where the tone that works on day 3 of an overdue is already wrong by day 90.

Why Sagepilot

Cityfurnish put an AI workforce on customer operations, organised the way a real team would be, with agents that each own a lane. Anjali runs inbound support across WhatsApp, Instagram, Messenger, and web chat, covering orders, KYC status, billing questions, refunds, and escalations that reach the right specialist team pre-briefed. Eight voice agents make the outbound calls that used to be manual: Tanya welcomes new signups, Ayushi walks customers through KYC and pickup, Meera schedules deliveries, Sneha rescues failed orders, Muskan handles extensions and pickups, Dev runs retention, and Priya and Vikram manage collections from early overdue through 90-days-plus recovery. Nisha manages the community on Instagram and Facebook. Underneath them, the workforce listens for lifecycle events, a cart abandoned, an invoice generated, a KYC rejected, a tenure ending, a payment overdue, and acts the moment one fires: the right message, email, or call, in the right order, before the customer has to ask.

The results

In the last 30 days, the AI workforce handled more than 275,000 lifecycle touchpoints across WhatsApp, email, and voice. Subscription renewals alone drove 38,000+ of them, referral flows fired 18,000+ times after invoices and deliveries, and abandoned carts were re-engaged 21,000 times. Overdue outreach now runs as a ladder from day 0 to day 300, seven bands deep, each with its own channel mix, and with voice joining at exactly the stages where a call outperforms a message. The human team stopped placing routine calls and re-answering the same invoice question, and now sees only the cases that genuinely need judgment, with the full story attached when they arrive.

Inbound · Billing and lifecycle support

The invoice question, settled in one reply

Anjali holds the inbound line across WhatsApp, Instagram, Messenger, and web chat. She verifies invoices and order state before answering, so “I already paid” becomes a clear explanation instead of an escalation to accounts, and nothing is ever promised without checking first.

Why am I getting a payment reminder? I already paid this month’s rent.

You’re right, Karan, this month’s rental invoice is fully paid. The pending amount is the one-time higher-floor carry charge from your sofa swap last week. Sending the exact breakup now.

Invoice and payment history verified first
Nothing stated without checking the ledger
Charge explained with the exact breakup

Billing confusion settled without touching accounts

Outbound voice · Failed orders

Sneha calls while the intent is still warm

When a payment fails at checkout, a saved cart quietly dies. Sneha calls within the hour, explains what happened, keeps the delivery slot held, and sends a fresh payment link on WhatsApp before the customer has moved on.

7:12

Rohan

Sagepilot AI · Sneha00:47

Hi Rohan! Your payment for the queen bed didn’t go through at the bank’s end.

Oh! Do I have to start over?

Not at all, your slot is held. I’ve sent a fresh payment link on WhatsApp.

mute

keypad

speaker

Failed orders rescued while intent is still warm

Proactive · Collections

A ladder from day 0 to day 300

Nobody at Cityfurnish chases payments by hand. The workforce watches every overdue account and escalates on its own through seven bands, each with its own message mix and tone. WhatsApp and email carry every band, and voice agents join in the earliest bands, when a call still changes the outcome.

Overdue outreach7 bands · live

BandChannels

Day 0-9

Day 10-37

Day 38-90

Day 91-120

Day 121-150

Day 150-210

Day 210-300

Voice joins the first bands, while a call still changes the outcome

One overdue ladder, day 0 to day 300

The workforce · Division of labour

Every stage has an owner

Not one bot stretched across every job. The workforce splits the lifecycle the way a real team would, from Tanya’s welcome call to Vikram’s 90-day recovery, with Anjali holding the inbound line and Nisha minding the community.

The Cityfurnish AI workforce10 agents

Anjali · Inbound support, every chat channel
Nisha · Community on Instagram and Facebook
Tanya · Signup welcome calls
Ayushi · KYC and pickup
Meera · Delivery scheduling
Sneha · Failed-order rescues
Muskan · Extensions and pickups
Dev · Retention
Priya · Collections and recovery
Vikram · 90-days-plus recovery

Each lifecycle stage has an owner

Onboarding

Going live

Phase 1 · Inbound on chat

Anjali goes live across WhatsApp, Instagram, Messenger, and web chat, trained on rental tenures, KYC requirements, billing, and refund policy.

Phase 2 · Proactive outreach

The workforce starts listening for order and billing events, signup, KYC, delivery, renewal, referral, overdue, and reaches out on WhatsApp and email the moment one fires.