AI-assisted customer service workflows

We install a service workflow around an assistant that reads each incoming query, looks up the order, delivery and customer record, drafts the reply and suggests a resolution. It routes every case to the right queue and flags the risky ones, such as repeat complaints or high-value accounts.

• A query taxonomy built from your past tickets, with a standard resolution for each type.
• A response policy covering tone, limits, credit bands and what always needs a manager.
• A drafting assistant connected to the order and delivery record.
• An approval step and an audit log of every draft, edit and send.
• A routing map with queues, owners and response targets.
• A cause report sent to operations each month.

• Customers wait less for a first reply.
• Your team sends more drafts as written, and the share sent as drafted is reported beside the share rejected.
• Credits follow the policy bands, so credit value per hundred orders reflects the policy rather than the person who took the case.
• More cases close at first contact, and the count of cases resolved at first contact shows it.
• Operations receives the cause behind complaints each month, and complaints per thousand orders are counted by cause.

Where each agent searches several systems for each query, response times lengthen at exactly the moment the customer is most frustrated. Answers vary between agents, credits are given inconsistently, and the cause of complaints never reaches the people who could remove it.

• Agents open three systems to answer one query.
• Two agents give different answers to the same complaint.
• Credit and refund amounts depend on who picked up the case.
• Complaints repeat every week for the same operational cause.
• You add service staff each time order volume grows.

Retailers, restaurant groups, delivery operators and marketplaces handling a high volume of order-status, missing-item and late-delivery queries across chat, email and social channels.

Qasim Abbas is the author of Moneyball Finance and reads a service automation as a spend decision before a technology one. Every assistant we install runs under a credit policy and an approver, so service spend is visible and capped before software touches it.

We work inside the service desk and CRM the group already uses, with order and dispatch records read from your systems. See how fees work.

How is quality kept up?

Through the audit log and a weekly sample reviewed by the service lead, with edit and rejection rates reported alongside.

What goes to operations?

A cause report each month that names the operational cause behind complaints, with complaints per thousand orders counted by cause.

Which queries does the assistant draft?

Order-status, missing-item and late-delivery queries across chat, email and social channels.

Give us a week of real tickets. We classify them with you and show the queries an assistant drafts for your team.