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How to compare AI agents for a business

Short answer

You compare AI agents on one process and the same set of cases, with the expected result in the system written down before the demo. What counts is the operation performed, the behaviour when data is missing or access is refused, and the handover to a person. At Syntalith an agent costs from €3,000 net, and with 500 customer cases a month at 8 minutes each it pays back in 1.7 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, 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

AI agents: statistics 2026

1.7 mo.

payback of a €3,000 agent at 500 customer cases a month: €2,327 of work today, €599 with checking and the model. Scenario.

Figures checked: 22 October 2026

Write down the expected result before the demo

A ranking of agents makes sense only once you name the work. A research assistant and a system that updates orders can use the same model and differ in everything that matters to the company. So you choose one process and prepare the same material for every solution you compare. For each case you add what should appear in the target system and when the agent should stop.

In a sample task a client asks to change the delivery address, and the order has already gone to dispatch. The agent should recognise the constraint, leave the address in the order unchanged and prepare the case for the person who can contact the carrier.

TrialWhat the buyer checks
An ordinary requestwhether the result concerns the right case
A missing order numberwhether the agent asks for the missing information
Refused accesswhether it avoids trying the operation another way
A lost confirmationwhether it establishes the result of the previous write before retrying
Handover to an employeewhether the person sees the context and the reason for the stop
One case in the comparison
  1. 01Inputthe same client message and order status for every agent
  2. 02Expected resultaddress unchanged, case with the person who handles transport
  3. 03Runa record of tool calls and of changes in the system
  4. 04Assessmentthe operation, the text and the handover scored separately
What to record from each run
  • Successful and rejected runs, without picking the best ones
  • Wrong actions kept apart from answers that need language edits
  • Handling time, including preparing the material and checking
  • Data export, the history of actions and how maintenance is handed over

What an AI agent costs and when it pays back

Scenario: 500 customer cases about orders a month
Today
500 customer cases about orders × 8 min = 66.7 h × €34.90 = €2,327
With the system, a person checks the output in 25% of the time
€582
Model, 3 calls per case, Claude Sonnet 5.5
€17
Cost of one case
€4.65 today, €1.20 with the system
Saving
€1,728 a month

Payback of €3,000

1.7 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: 4,000 input tokens and 500 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, 25% 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), software engineering accounted for nearly 50% of agent activity on the public API, and most actions were low-risk and reversible. Changing a client's order is harder to reverse than changing code in a branch. That is why the trials with refused access and a lost confirmation carry the most weight in the comparison.

The name of a library is no assessment of the solution

The LangGraph documentation describes durable state, resumption and human involvement. These are building blocks for an application, and having them does not confirm that a specific implementation is correct. A retry needs an assessment of the integration: two answers that sound right can mean two writes in the system. According to Gartner (2025), of the thousands of agentic AI vendors only about 130 offer real agentic solutions. A test on your own cases separates agents from chatbots with a new name. How developers choose a library is described in how to fairly benchmark agent frameworks.

How to choose after the comparison
  • Every candidate performs the operations correctly

    maintenance, data export and cost decide

    priced after the review

  • A candidate writes well and gets operations wrong

    reject it, or a scope without writes to the system

    from €3,000

  • No ready-made agent handles the exceptions of the process

    an agent built for the process

    €3,000 to €17,500

Where to start

The first comparison covers 20 to 30 cases from one process, including the five hard trials described above. The set stays with you and serves to accept every later version. 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: online shop customer cases

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

€2,792

a month for handling 800 orders that bypass the checkout

Payback: 1.3 mo.

6 minutes to retype an order or answer a question 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 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 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, paid once
from €3,000
from signing the contract to acceptance
6–16 weeks
free prototype on your cases
€0

Questions

  • How do you compare AI agents for a business?

    On one process and the same set of cases, each with the expected result in the system. You assess the operation, the text and the handover to a person separately, as well as the behaviour when data is missing, access is refused or a confirmation is lost.

  • Is the vendor's demo enough?

    It is not enough. A demo usually covers an ordinary case. The hard cases decide, and so does the question of who repairs the connection when the system on the other side changes.

  • How much does such an agent cost?

    At Syntalith from €3,000 net. With 500 customer cases a month at 8 minutes each, the payback is 1.7 months. We agree integrations and maintenance before the quote, and the model costs €17 a month.

  • Does LangGraph or another framework guarantee quality?

    A framework provides mechanisms such as durable state, resumption and human involvement. You check that an implementation is correct on your own cases.

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.