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AI for preparing a post-incident review

Short answer

After an incident, an AI agent combines the ticket, the team's conversations and the on-call notes into a timeline with a source beside every entry and a list of open questions for the people involved. The team establishes the cause and the actions at the review. The agent costs from €3,000 net at Syntalith and, with 30 post-incident reviews a month at 240 minutes each, pays back in 1.1 months.

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 agent for one process, build paid once
from €3,000
from signing the contract to acceptance
6–16 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

IT teams and AI: statistics 2026

1.1 mo.

payback of a €3,000 agent with 30 post-incident reviews a month: €4,188 of work today, €1,475 with checking and the model. Scenario.

Figures checked: 22 October 2026

What happened before the service came back

The service works again, and everyone brings a different story to the review. The on-call engineer remembers a phone call, the ticket holds the time of the alert, and the team chat describes several repair attempts. One person wrote that a restart helped, and a later entry reports further errors. In the end access returned after a setting was changed. A summary such as „a restart fixed the problem” would lose this sequence.

The agent builds a timeline with a source beside each entry and tells an observation apart from a later explanation. A change and an improvement that happen at the same time do not establish the cause. A difference between accounts need not mean a mistake, because the people involved watched different parts of the service, so the note keeps that difference instead of merging everything into one confident story.

Preparing a post-incident review
  1. 01Sourcesthe ticket, alerts, the team chat, on-call notes
  2. 02Timelineentries with the time and a link to the source
  3. 03Discrepanciesaccounts that differ, left unresolved
  4. 04Questionsspecific questions for the people involved, tied to entries
  5. 05Reviewthe team establishes the cause and the actions, the lead approves the description

What it costs and when it pays back

Scenario: 30 post-incident reviews a month
Today
30 post-incident reviews × 240 min = 120 h (€4,188)
With the system, a person checks the output in 35% of the time
€1,466
Model, 3 calls per case, Claude Sonnet 5.5
€9
Cost of one case
€139.60 today, €49.16 with the system
Saving
€2,713 a month

Payback of €3,000

1.1 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: 40,000 input and 3,000 output tokens per call at Anthropic's rates, converted at the ECB rate of 1.1205 USD per euro on 22 October 2026. The time covers collecting records from several channels, building the timeline and asking the people involved.

The count covers the work around a case: searching, reading, writing and passing things on. What remains is the time to check the output, 35% of today's work in the scenario. Before the quote we measure both times on 20 to 100 cases the team has already handled, in a €0 test that takes 5 working days.

Shorter preparation also changes the meeting itself. When the timeline is ready before the review, the team spends its time on the cause and on preventive actions. Without it, the first half of the meeting goes on working out who did what and when.

A ready-made summary still needs a conversation

Atlassian describes post-incident reviews in Jira Service Management, including a draft that Rovo prepares from the ticket details. If all the findings are in the ticket, that is enough. An agent makes sense when important information sits outside the ticket, in the chat and notes, and the review lead has to ask the people involved to fill in the same event.

What to choose for which incidents
  • All findings in the ticket

    a review draft in the ticketing tool

    licence

  • A few incidents a quarter

    the lead gathers the story by hand

    no build

  • Many incidents, findings in the chat and notes

    an agent that prepares the timeline and questions

    from €3,000

Where to start

The first scope covers one team and one type of incident. On a finished incident we compare the note with the participants' account: whether it surfaces the question that needed explaining, and whether a record stands behind every important claim. We build this as part of AI agents. For the free process review, a description of one case from recent weeks and the tools it ran through is enough. You do not need to send confidential documents, and you get a written plan within 2 working days.

Worked example · Scenario

How we count the payback: AI in an IT team

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

€4,188

a month for searching the documentation for answers to 600 questions

Payback: 0.8 mo.

12 minutes to find an answer or ask a colleague 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: Claude Sonnet 5.5, about 6,000 + 500 tokens per answer from the documents, 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 ↗

See the agent on your own cases before you commit.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 agents

See the agent on your own cases before you commit.

The agent takes the case through the next steps in your systems, and the actions take effect until the consent of the indicated person is obtained. A prototype for 20-100 cases that your team has already handled costs €0. We write down the purpose and test set in the contract.

See AI agents →
net per agent for one process, build paid once
from €3,000
from signing the contract to acceptance
6–16 weeks
free prototype on your cases
€0

Questions

  • How does an AI agent help after an incident?

    It combines the ticket, the team chat and the on-call notes into a timeline with a source beside every entry, and prepares questions for the people involved before the review.

  • Does the agent establish the cause of the incident?

    No. The agent shows the course of events and the discrepancies. The team establishes the cause and the actions, and the review lead approves the description for sharing.

  • How much does such an agent cost?

    At Syntalith from €3,000 net. With 30 post-incident reviews a month at 240 minutes each, the payback is 1.1 months. We agree integrations and maintenance before the quote, and the model costs €9 a month.

  • When is the ticketing tool enough?

    When all the findings are in the ticket. An agent makes sense when the story sits in the chat and in several people's notes.

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.