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ChatGPT for customer support: a rollout for support staff

Short answer

ChatGPT in customer service prepares a reply draft for the support agent from the ticket history and the company procedure, with a list of things to check before sending. At 800 tickets a month, cutting handling from 10 to 7 minutes gives 32 hours after deducting 8 hours of quality checks. At Syntalith a rollout for a team of up to 10 people costs from €1,150 net and pays back in 1.1 months.

net per day of closed training for the team
from €1,150
people in one training group
up to 15
after this time, we measure the effect on the same tasks
30 days
Book a free process review (30 min)

We belong to the OpenAI and Anthropic partner programmes and learn through their official courses. What this means ↓

Author: Syntalith · 3 min read

Example: the morning request inbox
Agent · ready

Statistics

AI in customer service: statistics 2026

32 h

a month is left for the team at 800 tickets, when handling drops from 10 to 7 minutes, after deducting 8 hours of quality checks. Scenario.

Figures checked: 22 October 2026

The procedure and the state of the specific case

A customer asks about a late delivery. The procedure describes what to do, and the current date is in the order system. ChatGPT needs both pieces of information for the reply to concern this case. If the status is missing, the result shows what the support agent has to check. A promise of delivery "tomorrow" must not come from an example reply in the instructions.

The same goes for a complaint: the procedure describes the rules, and the decision in a specific case has another source and another owner. The draft may quote the rule, but it may not grant a refund nobody has approved yet.

This scope concerns a tool for employees. A chatbot that answers customers has different requirements, and buying accounts for support agents does not launch it.

Where to start

  • A few categories, current instructions

    ChatGPT for support agents

    from €1,150

  • Many similar emails in one inbox

    triage and draft automation

    from €3,000

  • Customers write on the website at any hour

    a chatbot with handover to a person

    a separate project

The first scope of the rollout

Choose one category with current instructions, for example questions about the documents needed to start a service. Prepare the ticket history, the procedure and a template. Agree which customer data is really needed.

The result is a draft for the customer and an internal note with the gaps and the sources. The support agent checks that the reply takes into account the materials already supplied and does not ask again for a number already in the thread. ChatGPT Work uses files and approved connections, depending on the workspace settings (working with context). At the start you pass an approved extract of the ticket by hand, and you time that step too.

When a person takes over the case

Handing over a case
  1. 01ConditionA contradictory status, a missing document, a request for an exception, a case outside the procedure.
  2. 02ReasonThe handover says why the case stopped.
  3. 03DataThe information the next person needs is attached.
  4. 04OwnerA named person responsible for the case.

Permissions to refund money, change an order and send are set apart from reading the ticket. OpenAI describes the separation of reading, writing and sharing in the admin documentation. Add to the tests a customer message with an instruction that contradicts the procedure, no access to the status and an old version of a document. Check that the result flags the problem in place of hiding it in smooth text. Your own instruction in the conversation does not replace the access settings of the system, so the limits are enforced by the permission settings in the ticketing system.

What ChatGPT for customer service costs and when it pays back

Scenario: 4 support agents, 800 tickets a month
Saving
800 × (10 − 7) min = 40 h
Quality checks
8 h
Left
32 h (€1,117)
Licences
4 × $25 = $100 (€89)

Payback of a €1,150 rollout

1.1 months

The handling and checking times are the scenario's assumptions, which we replace with the team's measurement. €34.90 an hour is the EU average hourly labour cost for 2025 according to Eurostat. ChatGPT Business Standard with monthly billing from OpenAI's price list, converted at the ECB rate of 1.1205 USD per euro on 22 October 2026.

According to Brynjolfsson, Li and Raymond (2025), support agents helped by AI resolved 15% more issues an hour on average. In the same study, less experienced agents resolved 30% more. Judge the accepted reply together with looking up information and corrections. Watch reopened cases: a fast reply after which the customer writes a second time adds to the total work.

The cost of accounts and integration

Four Business Standard seats cost $100 a month (OpenAI pricing). A ChatGPT rollout for up to 10 support agents costs from €1,150 net, and training alone from €1,150 net a day. Our email handling system prepares a ready draft at foap.com for every email that needs an answer, with a median of 30 seconds, and has a build budget from €3,000 net. After launch, name an owner of the procedures and a person who reviews wrong drafts. When the service rules change, refresh the sources and check a set of example cases before the support agents start working on the new version. The choice between training, a feature of your current ticketing system and automation is described under AI in customer service.

This is how we implement it in companies

All case studies →

Client results.

All projects →
foap.comcustomer service

foap.com customer service: 95% of replies are sent automatically.

Users from several countries write to foap.com, in several languages. The system reads the entire conversation and the terms of that person, and then sends a response in that person's language. Questions about money and exceptions go to the team with a ready draft, so they have to check and send them.

the system sends the answers itself, without human typing
95%
time from the arrival of the e-mail to the ready response (median)
30 s
e-mails that require a response receive a ready-made draft
100%
less work for every 1000 answers (estimate)
47 h

Data from foap.com production, October 20-21, 2026. Estimate: 3 minutes for handwritten response.

How foap.com customer service works →
Sample messages. Money matters always come to the person.

Other implementations

jaktako.design

studio projektowe

−87%

Time to look for new customers, every day

4 hours → 30 min

approx. 73 hours less per month (21 days of work)

according to the studio

How the agent loop works →
Signature Estates

real estate

approx. −90%

Operator time spent browsing portals, per day

2–3 hours → 20 min

approx. 45 hours less per month (21 days of work)

respect · contact the seller 5 minutes after the announcement

How the agent finds property listings →
Kuba Koziej, CEO and co-founder of MoreGrowth and board member at Natu.Care

Kuba Koziej

CEO and co-founder, MoreGrowth

„We started with my own AI agent. During the training that followed, I learned to build new applications myself. Today I am bringing this way of working with AI into my business. Working with Syntalith gave me exactly the skills and tools I needed.”

View the original training review on LinkedIn ↗

Practice this on your team’s own tasks.Book a free process review (30 min) →

„I already use AI.”

Your people too. Just no rules.

From our conversations with companies

5 na 10 employees paste sensitive data into private AI accounts: contracts, invoices, customer data.

In ESET survey (2026)

1 na 10 admits this in the survey.

Customer data pasted into a private AI account without an data processing agreement is a violation of the GDPR.

Don't worry, we won't tell anyone :)

What do we see in companies that "already use"

  • Only ChatGPT or Claude accounts, without plugins, skills, integrations and MCP servers with company tools.
  • Company programs are not connected to AI. People still click through systems and Excel, and enter chat data manually.
  • Lack of company standards: everyone writes instructions in their own way, no one shares what works.
  • No rules for personal data, GDPR and company secrets.
  • No limits and no visibility: no one knows who uses AI, how much and for what.

62% Polish employees use AI at work · 27% companies have written rules for working with AI.

Source: ESET and DAGMA, Cyberportrait of Polish business 2026 (March 2026, 1,026 people) ↗

ChatGPT or Claude space review

Accounts, permissions, rules for working with data and 5 tasks set for the team. 1 day.

€450 net

ChatGPT rollout →Claude rollout →

Company accounts, rules of working with data and team training in 2 weeks, from €1,150 net.View implementation for the team →

„Is my data safe?”

Yes. You choose where they go: from your company account to the model on your server.

  1. 00Employee's private account

    Customer and company data ends up in an account that the company cannot see or control. There is no data processing agreement, so it is a violation of the GDPR. When an employee leaves, the chat history goes with them.

  2. 01ChatGPT or Claude corporate account

    The provider does not use your data to train models. A copy of the queries remains in his logs for up to 30 days.

  3. 02API with zero retention (ZDR)

    The provider processes the request and does not save anything. It requires his consent, we prepare the application together.

  4. 03Processing in the EU

    Queries are counted and stored in Europe: OpenAI in the EU region, Claude via clouds with the EU region.

  5. 04Model at your place

    The open model runs on your server or in your cloud in the EU. The data does not go outside the company.

What we do with every implementation

  • Confidentiality agreement and data processing agreement before we receive any data.
  • You choose the cases for the prototype and we anonymize them upon request.
  • The data stays in the EU and we delete it after the test.
  • Corporate accounts with an administrator on your side.

When data cannot leave the company

The open model runs on your server or in your cloud in the EU. To choose from:

White-tailed eagle
Polish model, SpeakLeash and ACK Cyfronet AGH
PLLUM
Polish model, HIVE consortium commissioned by the Ministry of Digitization
Qwen
Alibaba
GLM
Zhipu AI
DeepSeek
DeepSeek

We select a model for the task and check it on your cases. We run it, tune it and maintain it.

Source: Bielik and PLLuM, ACK Cyfronet AGH ↗ · PLLuM, Ministry of Digitization ↗

Do you have a lot of your own data? We will fine-tune the small model.

  1. 1 Your examples
  2. 2 tuning
  3. 3 test on new cases
  4. 4 model at your place

When you have thousands of similar emails, documents or reports, we teach a small open model based on your examples. It works for you, responds quickly and costs less to maintain than a large model. We measure quality on issues that the model has not seen while learning.

Przemysław and Piotr did it in large programming and consulting companies. Artem did it before and does it today at Syntalith. It's about models on your own infrastructure, tuning and quality measurement.

Private AI models →

Source: OpenAI, training on data from private accounts ↗ · OpenAI, who sees conversations ↗ · Anthropic, changes for private accounts (August 2025) ↗ · OpenAI, data in API ↗ · AWS Bedrock, EU profile ↗

You choose the protection level during the interview. We sign the data processing agreement before we see any data.Schedule a free analysis →

AI training for teams

Practice this on your team’s own tasks.

Closed training is conducted by engineers who implement AI systems themselves. We arrange the program according to the participants' roles and tools, and we measure the time of the same tasks before the training and after 30 days.

See AI training →
net per day of closed training for the team
from €1,150
people in one training group
up to 15
after this time, we measure the effect on the same tasks
30 days
Book a free process review (30 min)

or call+48 888 78 48 78WhatsAppMon–Fri 9:00–17:00 CET

Questions

  • How do I roll out ChatGPT in customer service?

    Choose one category of cases with current instructions. Prepare the ticket history, the procedure and a reply template. At the start, pass an approved extract of the ticket by hand, to check whether the draft is useful before connecting the ticketing system.

  • Do ChatGPT accounts for support agents launch a chatbot for customers?

    No. A tool for employees and a chatbot that answers customers have different requirements: availability, identifying the user and handing over cases. They are separate projects.

  • How much does ChatGPT for a support team cost?

    Four Business Standard seats cost $100 a month with monthly billing. At Syntalith a rollout for a team of up to 10 people costs from €1,150 net, with training on the team's tickets and a measurement after 30 days. At 800 tickets the payback is 1.1 months.

  • When does a person take over the case?

    With a contradictory status, a missing document, a request for an exception to the rules or a case outside the procedure. The handover gives the reason, the data needed and the case owner.

  • Does faster handling cut costs?

    Time given back is first room for backlog and harder cases. A financial saving appears when actual spending drops, for example on overtime or outsourced support.

Let's talk

Just write, call or choose a date.

We work fast because we hate corporate cotton wool. We don't have salespeople or managers to keep an eye on managers. You talk immediately to engineers who then build your system. We respect each other's time and yours too.

We will accept 3 more companies by the end of the year.

Write
contact@syntalith.ai
Call
+48 888 78 48 78
WhatsApp
write on WhatsApp

Mon–Fri 9:00–17:00 CET

What our OpenAI and Anthropic partnerships mean for you.

OpenAI makes ChatGPT and Anthropic makes Claude. We belong to the partnership programs of both companies, so we work with their tools every day and learn from the creators themselves.

OpenAI Select PartnerClaude Partner Network
01We will select a tool for the task
We implement both ChatGPT and Claude. We check both on your documents, and you choose the one that makes fewer corrections and saves more time.
02Knowledge straight from the creators
We learn from official OpenAI and Anthropic courses and materials. Your team learns about the features and settings that work today.
03Licenses without our margin
When we roll out ChatGPT, Claude or Copilot, you buy the licences directly from OpenAI, Anthropic or Microsoft and they invoice you. We add nothing to the licence.
04Certified engineers
On the team, we have an AWS certification in machine learning and an Anthropic certification in systems architecture on Claude.

Participation in programs does not mean that OpenAI or Anthropic endorses our services.