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Quality complaints: production is finished, the customer is waiting

Short answer

A quality complaint system brings together the work of production, quality and the account manager around an agreed reply package: photos, measurements and an explanation. A closed production task does not mean the package is ready. First check what your current quality system provides, and build an app when the client's package is put together from several departments' material outside that system.

How we workDetails ↓

  1. 01Call30 minutes with an engineer, free
  2. 02PrototypeA working system on your process and data, free
  3. 03ImplementationTarget and fixed price in the contract; 50% at signing
  4. 04Acceptance50% once the agreed target is met
net per application, fixed price before contract
from €3,000
from signing the contract to acceptance
4–10 weeks
free prototype on your documents
€0

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

Author: Syntalith · 5 min read

Example: the morning request inbox
Agent · ready

Statistics

Quality and AI: statistics 2026

1.2 mo.

payback of €3,000 at 150 complaints a month: €3,490 of work today, €1,048 with checking and the model. Scenario.

Figures checked: 22 October 2026

From complaint to reply
  1. 01Reportthe agreement with the client available to the team
  2. 02Actionsproduction and quality, with deadlines
  3. 03Packagephotos, measurements and the explanation
  4. 04Checkthe account manager before sending
  5. 05Replysent with the full set of material

Production's actions and the reply to a quality complaint

Say a client reported a finishing defect on parts from a specific batch. The company agreed with the client that the reply would include a description of the actions taken, photos and measurement results. Production did the assigned work and closed its task. The photos are in the team's folder, the measurement results in the quality system, and the account manager has a request for an explanation in their mailbox.

In the proposed app, the account manager opens, on the complaint, the agreed scope of the reply and the material shared by production and quality. They see what is still missing and whom to ask for it. The quality manager reviews the package before it is sent; they may ask, for example, for an explanation that photos of the work alone do not replace.

The reply sent and the later correspondence stay with the matter. When the client asks for extra measurements, the account manager passes the request to the right person. The team has access to the agreement it needs for further work and for closing the complaint later.

The agreements with the client have to be available to the team

The app can show on the complaint which material was agreed with this client, what has already been shared and who is preparing the missing part. A shared reply template can make the work easier, and it should allow for specific agreements. A request for an extra photo must not get lost just because every field of the standard form is filled in.

Your team names who approves the content of the reply and on what basis it treats the matter as finished. The quality assessment and the agreements with the client remain those people's job. AI can be considered separately for finding messages or tidying long correspondence; the flow of the complaint and its material can work without a model.

What your current quality system provides

In quality systems, the non-conformance register can refer to a customer complaint, a sales order or a batch. Corrective actions can have an owner, a deadline and documents. These are features of a ready product worth including when you assess your current solution.

Go through the last complaint where the account manager assembled the reply outside the system with the QMS administrator. Can the material be linked to the matter and shared with the person preparing the package? Can an extra request from the client be kept? If so, what you need may mainly be configuration and tidying the way of working. Include another product in the comparison too, if its flow fits your complaints.

An extension or integration makes sense when the QMS runs actions well, and the account manager has no convenient access to the material they need. The matter can be linked to documents in existing systems, with preparing the reply added for review. Before choosing the scope, confirm that the tools let you read the right batch and share the linked material with the right staff.

Your own workflow is worth considering when agreements with different clients keep needing work outside the available modules. A first project can cover a chosen group of B2B complaints, from receiving the report to the agreed closure. Rebuilding the whole QMS is not needed for that.

Open complaints after you change tools

During migration, the complaints that matter are those where the actions are done but the client is still waiting for a reply or an addition. A moved matter should keep the reference to the batch, the available material and the latest agreement with the client. The team can then carry on from the right point. Older complaints can stay in an accessible archive.

Settle whether a later export will cover these links together with the reply sent and the closing record. For your own app, also agree ownership of the code and data, and the documentation another supplier would need to take over upkeep.

After launch, the company still updates how it serves clients and names the people who check the material. The supplier's support should have an agreed scope, covering for example a document that is already in the QMS but did not appear on the complaint. Compare the build, moving open matters and later upkeep with configuring and supporting the current product.

Let us start with one reply to a client

For preparing the content of the reply, you can consider AI for complaint material and the 8D report. That scope helps gather sources for review; it does not confirm that production's actions were done or that they worked.

Start the conversation about your own complaint system with one matter and the agreements with its client. Use it to compare your current QMS with the proposed solution: will the account manager find the material they need, and will the quality manager assess the reply without gathering the history again? Such a review helps set the connections you need and decide whether extending the tool you use is enough. Syntalith's apps start from €3,000 net, and we set the scope after a free process review (pricing).

What a quality complaint system costs and when it pays back

Scenario: 150 complaints a month
Today
150 complaints × 40 min = 100 h × €34.90 = €3,490
With the system, a person checks the output in 30% of the time
€1,047
Model, 1 call per case, Claude Sonnet 5.5
€1
Cost of one case
€23.27 today, €6.99 with the system
Saving
€2,442 a month

Payback of €3,000

1.2 months

The volume, the time and the checking share are the scenario's assumptions. €34.90 an hour is the EU average hourly labour cost for 2025 according to Eurostat. Model: 3,000 input tokens and 300 output tokens per call at Anthropic's rates, converted at the ECB rate of 1.1205 USD per euro.

What we measure in the trial
  • Time from receiving a case to the result, before and after the change
  • Cases the app passed to a person
  • Corrections by the person checking
  • Model and maintenance cost at the target volume

Where to start

In the free process review we choose one process and count the team's volume and working time, and within 2 working days you get a written summary with a price. We build as part of AI apps, and we price maintenance separately.

Worked example · Scenario

How we count the payback: quality complaints

We run the same count for your plant in the free process review.

€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 →

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 ↗

When an off-the-shelf tool does not fit, we build your own.Book a free process review (30 min) →

How we build automation and agents

From a conversation to a working system in four steps.

  1. 01 · 30 min

    Free process review

    €0

    You're talking to an engineer. You receive the written plan within 2 business days.

  2. 02 · 5 days

    Free prototype

    €0

    The system works on 20-100 cases that your team has already handled. You see every result.

  3. 03 · 2–16 weeks

    Build

    50%

    Fixed price and goal written in the contract. First installment upon signing.

  4. 04 · after reaching the goal

    Reception

    50%

    You pay the second installment when the system reaches its target on your cases.

How a free prototype is created

Mon.

We set a goal

What result do you consider good?

Tue–Wed

The system is working

It goes through your affairs, one by one.

Thu

We compare

We check every difference with the team's work.

Fri

Result and price

List of errors and fixed implementation price.

You choose the matters. We anonymize them upon request, they stay in the EU and we delete them after the test.

On the market, such a test usually costs from PLN 3,000 to PLN 8,000.

Book a free process review (30 min)

We establish a prototype during a free analysis.

Data checked on October 25, 2026.

„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 →

Custom AI apps

When an off-the-shelf tool does not fit, we build your own.

We build an application with a language model for the work of your team: searching the company's knowledge, case panel or portal. We check the validity of your documents before launch, and the code stays with you.

See AI applications →
net per application, fixed price before contract
from €3,000
from signing the contract to acceptance
4–10 weeks
free prototype on your documents
€0

Questions

  • Why use a quality complaint system?

    So that the reply to the client is built from several departments' work in one place: the agreement with the client, production's actions, photos and measurements, and the explanation.

  • Can the quality system handle it?

    Quality systems usually have a non-conformance register with corrective actions, deadlines and documents. An app makes sense when the client's package is put together outside it.

  • How much does it cost?

    At Syntalith apps, automations and AI agents start from €3,000 net. At 150 complaints a month of 40 minutes each, the payback is 1.2 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.