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AI training for complaint analysis: comparing fault reports

Short answer

AI training for quality complaint analysts teaches them to compare complaints by model and operating conditions and to write a conclusion that keeps the observation apart from the cause. The key exercise is catching a draft that merges similarly worded complaints into one failure. At Syntalith team training costs from €1,150 net a day. With 6 people each saving 1.5 hours a week, it pays back in 0.9 months after licence costs.

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

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

Quality and AI: statistics 2026

0.9 mo.

payback of a €1,150 training at 6 people saving 1.5 hours a week each: €1,360 of time regained, €107 of licences a month. Scenario.

Figures checked: 22 October 2026

A shared symptom, different conditions

Several complaints describe a device that stops working. Some are about start-up, others about operation after a longer time. The draft prepared with AI merges them into one failure, and the summary reads well. The quality team, however, has to go back to the cases before deciding what to investigate next.

The analyst compares the conditions and notes that similar wording is not enough to merge cases. The review asks whether the author can explain the basis for the split and point to the record that contradicts it. ASQ describes stratification: dividing data into layers by source or conditions so that a pattern becomes visible.

A programme for complaint analysts
  1. 01Questionwhat the quality team wants to settle
  2. 02Layersmodel, operating conditions, period
  3. 03The customer's wordskept apart from later interpretation
  4. 04Conclusionthe observation and a question for further study
  5. 05Triala new set of complaints with no hints
A summary ready for the quality team
  • Every group has a basis for the split
  • A record that contradicts a group is pointed out
  • The observation is kept apart from the cause
  • Finding the cause stays with the technical investigation

What it costs and when it pays back

Scenario: 6 people after the training
Time saved
6 people × 1.5 h a week × 4.33 = 39.0 h
Value of that time
€1,360
Licences
$120 (€107)
Left after licences
€1,253 a month

Payback of a €1,150 training

0.9 months

The hours saved are the scenario's assumption, which we check by timing the tasks before the training and after 30 days. €34.90 an hour is the EU average hourly labour cost for 2025 according to Eurostat. Claude Team licences at $20 per person a month, at the ECB rate of 1.1205 USD per euro on 22 October 2026.

We measure the hours in the scenario before the training and after 30 days, on the same team tasks. If after a month checking AI texts takes as long as writing from scratch, we change the exercises or the scope of the tool.

According to a study in Science (2023), ChatGPT cut the time 453 professionals spent on writing tasks by 40%. In complaint reviews we also count the groups that had to be split after an expert's comments. We also count the complaints reopened after the review, because the fewer cases come back, the better the summary captured the differences.

When you need an analytics tool

If there are thousands of complaints and the questions repeat every month, consider a tool that groups the descriptions permanently. Training makes sense when analysts prepare the reviews themselves and need practice in reading an AI draft. A model can point to similar passages, but a person who knows the product judges what they mean. The wider scope is described in AI in quality control, and a model for grouping complaints in the article on sorting quality complaints.

Training, a tool or a model
  • Analysts prepare reviews themselves

    training on comparisons with AI

    from €1,150 a day

  • Recurring questions, high volume

    an app that groups complaints

    from €3,000

  • A ready-made model confuses categories

    a model adapted on assessed examples

    priced after a comparison

Where to start

With the quality manager we choose the question the team asks before a review and the examples approved for use. For the call, bring a summary after which the team had to go back to the complaints. We run the workshop as part of team training. For the free analysis, a description of one task the team does every week and of the tools it uses is enough. You get the written training programme within 2 working days.

Worked example · Scenario

How we count the payback: a quality team

We run the same count for your team in the free analysis.

€2,792

a month for collecting the evidence for 80 complaints

Payback: 1.3 mo.

1 hour to collect the evidence and draft a complaint report and checking in 15% of the old time are our assumptions. €34.90 an hour is the EU average hourly labour cost for 2025 according to Eurostat, for companies with 10 or more employees. Model cost: reading a photo at €0.0042 (0.004734 USD), measured in our field documentation system, plus the description (Claude Sonnet 5.5, about 2,000 + 400 tokens), at the ECB rate of 1.1205 USD per euro on 22 October 2026.

See the full calculation →

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.

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

Questions

  • What does AI training for complaint analysts teach?

    Comparing complaints by model, conditions and period, separating the customer's words from later interpretation, pointing to records that contradict a group and writing a conclusion with a question for further study.

  • Will AI establish the cause of a complaint?

    No. It can point to similar descriptions and suggest groups. The cause is confirmed by a technical investigation.

  • How much does such training cost?

    At Syntalith from €1,150 net for a day of workshop for the team. Claude Team licences cost $20 per person a month. With 6 people saving 1.5 hours a week each, the payback is 0.9 months.

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.

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.