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ERP Order Entry: When n8n Is Enough

Short answer

You turn an order written in the customer's words into item codes and quantities with rules: matching to the catalogue, converting units and deciding on substitutes. Unclear lines go to an operator. An agent is needed only when the agreed path is not enough. At Syntalith an automation costs from €3,000 net, and with 1,000 orders a month at 6 minutes each it 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 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

Orders and automation: statistics 2026

1.1 mo.

payback of a €3,000 automation at 1,000 orders a month: €3,490 of work today, €706 with checking and the model. Scenario.

Figures checked: 22 October 2026

What to do with three boxes of gloves

A salesperson receives an order: „three boxes of gloves”. The code first looks for a confirmed product in the catalogue. A full name gives a match, and a shortened or ambiguous description stays a candidate to check. Three boxes of a hundred give three hundred units in the draft, and the operator sees the conversion. An unknown unit and an unavailable product that needs a substitute go to the operator, because consent to substitutes is not consent to any item code.

In the demonstrator these decisions are three separate functions: catalogue matching, reading the unit and the substitute decision. Each can be right or wrong independently. The operator picks the item code, confirms the unit and records the reason. Repeating the same decision is rejected, and an order with an unresolved line does not go to export.

Order intake in the Syntalith demonstrator
Local demonstrator, 25 September 2026. Synthetic data, decisions saved in a local database.
An order line
  1. 01Cataloguea full name gives a match, a short form stays a candidate
  2. 02Unitthree boxes of a hundred are three hundred units
  3. 03Substituteonly from the allowed list, otherwise the operator decides
  4. 04Operatorpicks the item code, the unit and the reason
  5. 05Exportonly orders with no open lines
The scope of the evidence
  • 25 September 2026: 12 matches, 5 conversions and 4 substitute decisions, 21 of 21 passed
  • 9 October 2026: 9 new cases, all with the expected result
  • A negative quantity passes through the conversion function, so input validation has to be added
  • No model calls, no n8n and no external order system

What order intake automation costs and when it pays back

Scenario: 1,000 orders a month
Today
1,000 orders × 6 min = 100 h × €34.90 = €3,490
With the system, a person checks the output in 20% of the time
€698
Model, 1 call per case, Claude Sonnet 5.5
€8
Cost of one case
€3.49 today, €0.71 with the system
Saving
€2,784 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: 2,500 input tokens and 400 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, 20% 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.

The confidence field in the demonstrator holds constants written into the code. In a rollout, we measure reading confidence separately on the client's orders.

Do you need n8n, AI or a feature of your current system

If orders arrive in a file with fixed columns and correct item codes, check the import in your current order system: a model has nothing to recognise there. When data has to move between several tools and the conditions are known, an n8n flow is enough: the If node splits cases by conditions, and HTTP Request calls an API. AI is worth testing when a customer writes a free-text message from which the lines have to be extracted. Converting boxes into units is an ordinary rule.

Import, rules, AI or an agent
  • A file with fixed columns and item codes

    the import in your current system

    configuration

  • Known conditions, several tools

    a flow with rules and operator decisions

    from €3,000

  • Free-text messages from customers

    an AI step that reads the lines before the rules

    from €3,000

Where to start

Start with one order channel and writes to a test environment. To prepare: the current catalogue, units and pack sizes, and sample orders with the correct result. The demonstrator's screens are on the page order intake. We build this kind of rollout as part of AI automations. 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 intake

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 →

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

  • Do you need an AI agent to take in orders?

    Usually you do not. Rules handle catalogue matching, unit conversion and substitutes, and unclear lines go to an operator. AI helps to read free-text messages, and an agent only for decisions outside the agreed path.

  • What did the demonstrator test show?

    21 of 21 cases passed on 25 September 2026, and 9 of 9 new ones on 9 October. A trial with a negative quantity showed that input validation has to be added before production use.

  • How much does such an automation cost?

    At Syntalith from €3,000 net. With 1,000 orders a month at 6 minutes each, the payback is 1.1 months. We agree integrations and maintenance before the quote, and the model costs €8 a month.

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.