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Calculating exception-handling costs in automation

Short answer

The cost of exceptions is people's work on the cases an automation did not finish by itself: filling in data, retrying and checking the result. You count it per case, with all of its runs together. At 3,000 orders a month and 15% exceptions at 10 minutes each, that is 75 hours. A completeness check that lowers the share to 5% pays back in 1.7 months at a price of €3,000.

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 for the automation of one process, build paid once
from €3,000
from signing the contract to acceptance
2–6 weeks
free prototype on your cases
€0

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

Automation and exceptions: statistics 2026

75 h

a month go on exceptions at 3,000 orders, when 15% need 10 minutes of work. A drop to 5% gives back 50 hours, which is €1,745. Scenario.

Figures checked: 22 October 2026

A retry does not create a new case

An order from the portal stops on incomplete data. An employee writes to the account manager, adds the information and retries the handover. After another error she comes back once more. The technical history has several attempts, while for the team it is one case with several interventions.

One case, several interventions
  1. 01StopThe automation stops the order because data is missing.
  2. 02ClarificationThe employee contacts the account manager.
  3. 03RetryShe adds the information and retries the handover.
  4. 04Second errorA different reason for the stop, another return to the case.
  5. 05CloseThe report counts all the work on one order.

The report gathers the effort on the shared order and shows the attempts one after another. Otherwise the number of handled cases grows with every retry, and the hard cases disappear into the average. The reason for the first stop can differ from the next one, so grouping by the last error is not enough.

Working time is different from waiting time

An order may have waited overnight for a reply, while the employee spent a few minutes on it. The gap between events in the system does not give you her working time. If the company does not record it, the report shows a gap or an estimate agreed with the team. Without this distinction a case that waited a day looks the most expensive, although it took five minutes of work.

What exceptions cost

Scenario: 3,000 orders from the portal a month
Exceptions today
3,000 × 15% = 450 cases × 10 min = 75 h (€2,618)
After a completeness check
3,000 × 5% = 150 cases × 10 min = 25 h
Time given back
50 h (€1,745) a month

Payback of a €3,000 fix

1.7 months

The volume, the share of exceptions and the handling time are the scenario's assumptions, which we check against the order history. €34.90 an hour is the EU average hourly labour cost for 2025 according to Eurostat. A cash saving appears when the company cuts real spending, for example overtime.

In the count, also write down whether the result covers only day-to-day handling, or also the analysis and repair of the automation itself. Mixing the two without a note makes it hard to compare one month with the next. The manager also needs the distribution. The same number of exceptions can mean many short fixes or a few long negotiations. A view of individual cases lets you check where the result comes from before you choose a change.

What the tools already show

Microsoft Power Automate Process Mining has rework metrics, including direct repetitions and returns after other steps (rework metrics documentation). If your current tool shows repetitions on the same case, use that view. A separate connection is needed when interventions stay in tickets, messages or timesheets outside the process history.

Where the missing effort is
  • Repetitions in the process history

    a process mining tool

    an existing view

  • Interventions in tickets and emails

    sources joined in a report

    from €3,000

  • Free-text descriptions of interventions

    AI sorts the topics, with the original beside them

    from €3,000

Order a report that helps you choose the fix

The first scope covers one automation and a chosen period, usually the last quarter. The client points to the places where employees record interventions and agrees what goes into the count. Syntalith links the attempts to real cases and prepares an effort report, as described for reporting automation. For the first conversation, one case is enough: one the automation finished and the team handled several times.

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 ↗

This process can go on its own. You will check this on your cases before you pay.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 →

AI automations

This process can go on its own. You will check this on your cases before you pay.

The system takes over repetitive work from emails, documents and spreadsheets, and hands over uncertain matters to a human. A prototype for 20-100 cases that your team has already handled costs €0. You pay the other half of the price when the system reaches your goal.

See AI automations →
net for the automation of one process, build paid once
from €3,000
from signing the contract to acceptance
2–6 weeks
free prototype on your cases
€0

Questions

  • How do we calculate the cost of exceptions in an automation?

    Number of cases × share needing intervention × time to handle one exception × cost of an hour. You count each case once, and its time covers every intervention and retry, without the time spent waiting for a reply.

  • Why does the automation report not show people's work?

    The technical history counts runs and error messages, while people's work stays in tickets, messages and timesheets. For the system a retry is a new run. For the team it is the same case.

  • How much does it cost to improve exception handling?

    Automating a report or a completeness check costs from €3,000 net at Syntalith. In the scenario with 3,000 orders, a drop in exceptions from 15 to 5% gives back 50 hours and pays back in 1.7 months.

  • Do process mining tools show this?

    Microsoft Power Automate Process Mining has rework metrics. They help find work that is done again, but they cannot supply human effort that never enters the process history.

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.