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Which SaaS workflow should you replace first?

Short answer

The first stage of moving away from SaaS covers a part of the work with a clear boundary: you know which work moves to the new application, where it takes its data from and what stays in the old system. Without that boundary, a partial replacement creates two places that handle the same case.

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 application, fixed price before contract
from €3,000
from signing the contract to acceptance
4–10 weeks
free prototype on your documents
€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

Replacing SaaS step by step: statistics 2026

3.1 mo.

payback of €3,000 at 300 cases a month: €1,396 of work today, €422 with checking and the model. Scenario.

Figures checked: 22 October 2026

AWS describes the strangler fig pattern: new features take over parts of the old system one by one, until the old one can be switched off. With SaaS it works in a similar way, but each part needs its own data boundary, because a correction saved only in the old system will give the employee out-of-date materials.

The boundary of the first scope
  • Which work moves to the new application
  • Where the application takes data from and where it saves it
  • Which system is the source for each piece of information
  • An owner of the switch on both sides

The first scope has to be separable

Suppose a service company runs clients, quotes and delivery in one package. Preparing documents after a finished service takes the most manual work. The team is considering its own workflow for these materials, keeping quotes and planning in the current tool.

Such a split can be clear: a finished job with the client's identifier goes to the document application, and the person responsible prepares the package. You still have to decide what happens when the job is reopened. If the correction stays only in the old system, the employee may hand over out-of-date materials. This dependency belongs to the first scope, even if it occurs less often than an ordinary finish.

A good candidate has an understandable start, a result the recipient needs and a person responsible for the whole. You can name which information will be read from the current tool and which new records will be created outside it. When almost every step needs a record changed in both places, the boundary needs rethinking.

The choice does not have to fall on the most irritating feature. Sometimes it is so tightly linked to the rest of the package that separating it drags in a large part of the system. Compare several candidates by how much the problem matters, the dependencies and how the result can be checked. A smaller area can give the company experience in ordering and maintaining its own software.

Two systems need agreed cooperation

AWS describes gradually replacing a system's features in the strangler fig pattern: the old and new parts coexist during the switch. The description concerns application modernisation and has defined technical limits. With SaaS, whether such a split is possible has to be checked separately in the available integrations and the terms of the service.

Before you build, ask the current product's vendor whether configuration or an available add-on will solve the chosen problem. Your own part can also stay a permanent extension, if the rest of the package serves the company well. Deciding on the first stage does not commit you to rebuilding every feature later.

In the cost comparison, include the period when both tools work together. Access to the old system, the connections and help for users may still be needed. Do not assume that launching one application will automatically reduce your commitment to the SaaS vendor. That depends on the terms of use and on who still needs the product.

The switch has an owner on both sides

Open cases need a clear decision on where they will be finished. In the example, the company can leave started document packages in the old flow and send new ones to the application, or agree to move them. An employee should be able to check the right place easily, without comparing two lists.

The order should cover how missing updates are clarified and who is responsible for the connection. Also settle access to the code, the documentation and a data export with references to the original jobs. Then the next stage or a change of contractor does not require working out the meaning of the records from scratch.

Talk to Syntalith about the task your team most often does outside SaaS. Using it as the example, we can discuss the boundary of the first scope, the dependencies and the terms for keeping the rest of the system. Pricing information is on the pricing page.

What it costs

Scenario: 300 cases a month
Today
300 cases × 8 min = 40 h (€1,396)
With the system, a person checks the result in 30% of the time
€419
Model, 1 call per case, Claude Sonnet 5.5
€3
Cost of one case
€4.65 today, €1.40 with the system
Saving
€974 a month

Payback of €3,000

3.1 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: 3,000 input tokens and 300 output tokens per call at Anthropic's rates, at the ECB rate of 1.1205 USD per euro on 22 October 2026.

What we measure in the trial
  • The time from receiving a case to the result, before and after the change
  • Cases the application passed to a person
  • Corrections by the person checking
  • The cost of the model and maintenance at the target volume

Where to start

In the free review we choose one process and count the volume and the team's working time, and within 2 working days you receive a written summary with a price. We build the automation as part of AI automations, from €3,000 net.

Worked example · Scenario

How we count the payback: the first scope

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

€4,363

a month for handling 1,500 job emails

Payback: 0.8 mo.

5 minutes to read an email and reply 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 3,000 + 600 tokens per message with a draft reply, 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 ↗

When an off-the-shelf tool does not fit, we build your own.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 →

Custom AI apps

When an off-the-shelf tool does not fit, we build your own.

We build an application with a language model for the work of your team: searching the company's knowledge, case panel or portal. We check the validity of your documents before launch, and the code stays with you.

See AI applications →
net per application, fixed price before contract
from €3,000
from signing the contract to acceptance
4–10 weeks
free prototype on your documents
€0

Questions

  • Where do you start replacing SaaS?

    With a part of the work that can be separated: with a clear input, result and owner. The rest stays in SaaS, and the two systems exchange only agreed data.

  • Can you replace SaaS step by step?

    Yes, part by part, if each part has a boundary, an owner on both sides and a rule on which system is the source of the data.

  • How much does it cost?

    At Syntalith, AI apps, automations and agents start from €3,000 net. At 300 cases a month and 8 minutes each, the payback is 3.1 months.

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.