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AI notes: the cost of a tool and an integration

Short answer

A plain meeting summary often comes from a tool the company already uses, once the licence and settings are checked. You pay separately when approved decisions have to reach the CRM or a project tool as tasks with an owner and a deadline. Such an automation costs from €3,000 net at Syntalith. At 120 meetings a month it pays back in 2.5 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 for the automation of one process, 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

AI meeting notes in companies: statistics 2026

2.5 mo.

payback of a €3,000 automation at 120 meetings a month: €1,396 of retyping by hand, €214 with checking and the model. Scenario.

Figures checked: 22 October 2026

First check what you already have

The cost of AI notes depends on where the work ends. If a summary to read is enough for the team, a tool the company already uses usually provides it. Microsoft describes Intelligent recap in Teams as a feature that depends on a Teams Premium or Microsoft 365 Copilot licence and on the transcription policies.

A tool or an integration
  • A summary to read after the meeting

    a feature of your current tool

    licence

  • Learning to check draft notes

    team training

    from €1,150 a day

  • A task list for approval with the part of the conversation

    automation

    from €3,000

  • A task saved in the right case in the CRM

    automation with a write

    from €3,000

The administrator checks the specific meeting type, the accounts and the features needed. One person's licence need not give every participant the same view. Settle the rules for recording and for access before you switch the feature on.

A summary and a task are two different checks

In the meeting someone says „I'll try to prepare the quote by Friday”, and later „I'll confirm the date after talking to the supplier”. A draft task with a firm Friday deadline drops the condition. The person checking must see both parts and be able to leave the deadline unconfirmed.

What the integration does after a meeting
  1. 01TranscriptIt takes the transcript from the tool the company already uses.
  2. 02DecisionsIt lists the tasks with the part of the conversation they come from.
  3. 03UncertaintyIt marks a deadline or an owner that nobody confirmed.
  4. 04ApprovalThe person who ran the meeting corrects and approves the list.
  5. 05Write to the CRMThe task goes to the right case, with no duplicate when the meeting is processed again.

A name mentioned in the conversation need not mean the person responsible. Before the integration gets the right to write, settle who approves the fields and what happens after a note is corrected.

What it costs and when it pays back

Scenario: 120 meetings a month, decisions go to the CRM
Today
120 meetings × 20 min = 40 h (€1,396)
With the system a person checks the output in 15% of the time
€209
Model, 1 call per case, Claude Sonnet 5.5
€4
Cost of one case
€11.63 today, €1.78 with the system
Saving
€1,182 a month

Payback of €3,000

2.5 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: 15,000 input tokens and 800 output tokens per call at Anthropic's rates, at the ECB rate of 1.1205 USD per euro on 22 October 2026. We took the transcript of a 45-minute meeting as 15,000 tokens.

The model is the smallest item here. The result depends on the time someone spends today retyping decisions, and on how much of it is left for checking.

Compare proposals for the same result

ScopeWhat to compare in the budget
A summary in your current toolAccounts, settings and access to the material
Learning to check notesThe workshop programme and the participant's own trial
A list for approvalSources of the decisions, corrections and roles
A write to the systemMatching the case, confirming the operation and retries
Further workUpkeep after a tool change and error handling

If the team already has the right tool and the problem is checking drafts, start with team training. The workshop covers neither licences nor a connection to the CRM.

How to test the flow before launch

A trial before you buy
  • A meeting with an unconfirmed deadline
  • A decision withdrawn later in the same meeting
  • Two similar projects that are easy to mix up
  • Processing the same meeting again without creating a second task
  • Access to the summary compared with access to the recording

The person who receives a task often needs only a short decision, without the whole conversation. The scope of sharing is the process owner's decision. For a conversation about AI notes and minutes, bring the type of meetings, their number a month and the place you retype decisions into today. A recording is not needed to agree the scope.

Worked example · Scenario

How we count the payback: meeting notes in the CRM

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

€1,745

a month for writing notes after 150 meetings

Payback: 1 mo.

Our assumptions are 20 minutes for the note and task list after a meeting, and checking in 25% of the old time. €34.90 an hour is the EU average hourly labour cost for 2025 according to Eurostat, for companies with 10 or more employees. Licence: ChatGPT Business or Claude Team at 20 USD per person a month on annual billing, about €17.85 at the ECB rate of 1.1205 USD per euro on 22 October 2026. We count the whole licence against notes here, although the team also uses it for other work. Rollout: from €1,150 for up to 10 people, from €2,300 for 11 to 40 people.

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 ↗

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 21, 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, paid once
from €3,000
from signing the contract to acceptance
2–6 weeks
free prototype on your cases
€0

Questions

  • How much do AI meeting notes cost?

    A summary in Teams or another tool you use needs the right licence and settings, which the administrator checks. Passing approved tasks to the CRM is an automation from €3,000 net. The model costs about €4 a month at 120 meetings.

  • Does Teams take meeting notes by itself?

    Microsoft describes the Intelligent recap feature, which depends on a Teams Premium or Microsoft 365 Copilot licence and on the transcription policies. Check the meeting type and the accounts before you buy another tool.

  • When is an integration needed?

    When someone retypes the decisions into the CRM or a project tool after the meeting and assigns an owner and a deadline. The integration prepares these tasks for approval and saves them in the right case.

  • Who is responsible for a wrong deadline in a note?

    The person who approves the task list. That is why the system shows the part of the conversation next to each decision and marks a deadline nobody confirmed.

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
You buy accounts directly from OpenAI or Anthropic and receive an invoice from them. We do not add anything to the license.
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.