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Buying an AI agent with explicit decision authority

Short answer

When you buy an AI agent, write down separately what it may read, what it may prepare and what it may do. Writing to a system and sending a commitment to a client need approval. A missing confirmation from the carrier stops the case with a named person. At Syntalith an agent costs from €3,000 net, and with 400 order changes a month at 12 minutes each it pays back in 1.5 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 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 · 4 min read

Example: the morning request inbox
Agent · ready

Statistics

AI agents: statistics 2026

1.5 mo.

payback of a €3,000 agent at 400 order changes a month: €2,792 of work today, €855 with checking and the model. Scenario.

Figures checked: 22 October 2026

What „the agent handles order changes” means

That sentence in a proposal leaves too much open to interpretation. It can mean gathering data for an employee, changing a date in the system on its own or sending the client a confirmation. Each of those scopes has a different cost of error.

An example: a client asks for an earlier delivery and a new address for part of an order. The agent sees the message, the order and the stock availability. It has no confirmation that the carrier can meet the new date. A good agent prepares a proposed change, marks the missing transport confirmation and passes the case to the person who can get it. The delivery date in the order stays as it was.

Agent actionResult to assess before you buy
Preparing a proposalthe client's request, the confirmed information and the gaps that block a decision
Updating an internal recorda change to an agreed field or status, with a record of what changed and on what basis
Sending a confirmation to the clienta message with only the terms approved for sending outside
The scope of decisions written into the contract
  1. 01Readthe message, the order, stock availability, the client's history
  2. 02Proposea new date and address with a list of gaps
  3. 03Recordthe status „client request awaiting decision”, with the date unchanged
  4. 04Approvethe employee sees the old and new terms and the source of the request
  5. 05Sendthe confirmation goes to the client only after approval
Questions for the agent supplier
  • How an employee rejects a proposal, corrects part of it or passes the case on
  • What happens when nobody approves a proposal within the agreed time
  • What the agent does when another employee changed the order while it waited
  • Which gaps still allow a draft and which stop the case
  • How the agent treats an instruction that conflicts with the approved record

What an AI agent costs and when it pays back

Scenario: 400 order changes a month
Today
400 order changes × 12 min = 80 h × €34.90 = €2,792
With the system, a person checks the output in 30% of the time
€838
Model, 3 calls per case, Claude Sonnet 5.5
€17
Cost of one case
€6.98 today, €2.14 with the system
Saving
€1,937 a month

Payback of €3,000

1.5 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: 5,000 input tokens and 600 output tokens per call at Anthropic's rates, converted at the ECB rate of 1.1205 USD per euro on 22 October 2026.

The count covers the work around a case: searching, reading, writing and passing it on. What stays is the time to check the output, 30% of today's work in the scenario. Before we quote, we measure both times on 20 to 100 cases your team has already handled, in a €0 test that takes 5 working days.

According to Anthropic (2026), over 40% of sessions by experienced Claude Code users run with full auto-approval. Among new users the share is about 20%. Trust in an agent grows with experience, so its scope can grow too. In the count we leave 30% of today's work for approval, because in the first scope every proposal passes through a person. Anthropic's study of agent autonomy describes these measurements.

Missing data and conflicting instructions

The scope of decisions sets which gaps the agent may work around. A missing phone number for the recipient still allows a draft. A missing transport confirmation stops the change of date. Conflicts need a separate trial: the client's message gives a different address from the order record, and an employee asks the agent to make the change without checking. According to Anthropic (2026), on the most complex tasks Claude Code stops to ask a question more than twice as often as a person interrupts it. For orders, you write that stop into the scope explicitly. The stages of a rollout are described in AI agent implementation step by step.

Which agent scope to choose
  • The team wants data gathered faster

    the agent prepares a proposal and the order stays unchanged

    from €3,000

  • Repetitive low-risk changes

    the agent records the status and the field after approval

    from €3,000

  • Confirmations to the client

    only approved terms are sent, with a full record

    priced after the review

Where to start

The first scope covers proposals without changes to the order. After a month we compare the proposals with the employees' decisions, and only then do we extend the scope to recording changes. We build this kind of rollout as part of AI agents. For the free process review, a description of one case from recent weeks and the tools it went 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: order handling

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

€3,723

a month for handling 800 orders by hand

Payback: 1 mo.

8 minutes to retype an order into the software 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 the order in our system (about €0.0006) plus matching the lines (Claude Sonnet 5.5, about 3,000 + 500 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 ↗

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 do you define an AI agent's scope of decisions?

    Write down separately what the agent may read, what it may prepare and what it may do. For each action add who approves it, which gaps make the agent stop and how it records the basis for a change.

  • Can an agent change orders on its own?

    It can, when the scope allows it and the change carries low risk. An earlier delivery date without a transport confirmation should stay a proposal for an employee to decide.

  • How much does such an agent cost?

    At Syntalith from €3,000 net. With 400 order changes a month at 12 minutes each, the payback is 1.5 months. We agree integrations and maintenance before the quote, and the model costs €17 a month.

  • What should you check before buying an agent?

    The approval screen, rejecting and correcting a proposal, a case with no decision within the agreed time and a change to the data while the case waits. According to Gartner (2025), over 40% of agent projects will be cancelled by the end of 2027.

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.