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AI customer service

AI Customer Service Agent - Tickets and Escalation

AI customer service agents handle repetitive questions, classify tickets, draft answers and keep priorities under control. They work with the company knowledge base, contact history and escalation rules. Your team spends less time on the same cases, and customers receive a faster answer or reach the right person sooner.

A helpdesk agent for one process is PLN 5,000-15,000 net. A setup with several agents and CRM is PLN 20,000-80,000 net.

Pricing

What it costs

An agent for one request channel costs 5-15k PLN. A system on several channels and with escalation to a human costs 20-80k PLN. This scope is tickets and escalation: request classification, reply drafts and priorities, and for a wider system several agents with CRM - not a site widget.

One helpdesk process5-15k PLN

A ticket agent: classification of requests, reply drafts, priorities. Deployed in a few working days.

Multi-agent system20-80k PLN

Several service agents with CRM integration, context memory and escalation rules to a human.

Helpdesk agent and multi-agent system - scope, time and cost
ChannelDeployment costDeployment timeWhat it handles
One helpdesk process5-15k PLNA few working daysTickets, request classification, reply drafts, priorities
Multi-agent system20-80k PLNQuote after a free call about the ticket queueSeveral service agents, CRM integration, context memory, escalation to a human

Pricing follows a free call about the ticket queue. We don't charge for the first call or the scope proposal. Prices current as of August 2026.

Who it is for

Tickets, drafts and escalation

For companies where customer service is blocked by emails, ticketing, repeated questions and manual data entry.

Scope

Helpdesk agent, automatic classification, response suggestions, SLA priorities, CRM, knowledge base and quality reports.

Outcomes

What changes in the helpdesk

The deployment starts with real customer tickets. This makes the agent respond to actual problems, not a made-up demo scenario.

01

Faster first response

02

Less manual ticket sorting

03

More consistent answers

04

Reports of customer topics and issues

Process

How we work

01

Ticket analysis

We take a sample of emails or tickets and group common customer intents.

02

Rules and knowledge base

We define what the agent can solve alone, what it can suggest and what must go to a human.

03

Controlled start

The agent first works as a team assistant, then selected categories can become automatic.

What the agent does

A helpdesk agent for the ticket queue

The agent works in the support queue: it classifies tickets, drafts replies, keeps reply times in order and writes a note back to the CRM. If the pain is a chat bubble on the website, that is a site widget, not this agent.

Next step

The deployment starts with real customer tickets. This makes the agent respond to actual problems, not a made-up demo scenario.

A helpdesk agent starts on a live ticket sample: intents, priority rules and what must stay with a human. Assistant mode comes first. Automatic close is only for categories that already pass the quality log.

Helpdesk agents, not a site widget

How an AI agent enters a ticket queue

The job is the support queue: classify the ticket, draft a reply, escalate what a person must take, and write the outcome back to the CRM. This is not a chat bubble on the website.

01

Start from real tickets, not a demo script

We ask for a sample from the current helpdesk or mailbox and group the intents customers already send. Status questions, simple complaints, policy lookups and billing repeats are usually the first candidates. Strategic accounts, legal threats and anything that needs a commercial exception stay with people.

The first production shape is assistant mode. The agent drafts a reply and a category. An agent on the team accepts or edits. Only after the log shows a stable category do we allow an automatic send for that category alone.

02

Priority and history matter more than fluent text

A keyword macro cannot see that the same customer wrote yesterday, that the order is already refunded, or that the case is a duplicate. The agent needs contact history, ticket fields and the knowledge base the team already uses. Without that, it only writes faster noise.

The business result is a cleaner queue: urgent cases rise, duplicates fold, the draft is waiting, and a manager can see which topics come back every week. That is operations, not a marketing chatbot.

03

How the agent writes into the case

The agent writes into the existing case. It does not open a second inbox and it does not become a public chat.

If you need a site widget instead, that is a chatbot on the website. If you need agents on mail and orders rather than tickets, that is a process agent. Here we stay on the helpdesk queue.

AI customer service

FAQ

Common questions about ai customer service agents - scope, deployment, data, cost and security.

Yes, but we usually start in assistant mode. After quality checks, the agent can handle selected categories automatically.

Yes. We integrate agents with CRM, ticketing, email, Slack, Teams and custom systems through APIs.

That is not the assumption. The best effect comes from removing repetitive work and leaving complex cases to people.

Available for new projects

Next step

See if an agent can take the ticket queue

Tell us how tickets arrive and who triages them today. We will return with an agent scope, escalation rules and an estimate for the helpdesk layer.

Book a free call