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When to retire a custom SaaS extension

Short answer

You retire a custom SaaS extension when the vendor's new feature covers the user's whole working day, including the agreements that a short feature description does not show. You assess it as a separate change: on the same cases, with a plan for moving the data and switching the add-on off.

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

SaaS extensions: 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

The extension was built because the system lacked a feature, and over the years it may have taken on more work than its description says. A short description of the vendor's new feature usually covers the main case, while the exceptions stay in the extension. Before the shutdown, the process owner names the ones that are still needed.

Configuration, an extension or a custom application
  • The feature exists in the current system

    configuration or a plan change

    a licence

  • One step is missing

    an extension of the current system

    from €3,000

  • Workarounds in every case

    a custom application for one process

    from €3,000

The new feature covers part of the old need

Suppose a company commissioned an application that sends notifications about changes in a register. Over time it was extended with a reminder to the manager if the named person had not picked up the case. Now the current tool offers its own notifications. The administrator sees a chance to simplify support, but the manager still needs to know about cases left without a response.

First establish which behaviours are actually used. Ordinary notifications may be enough, because the team has changed the way it works. The reminder you need may be configurable in the product. You can also keep only the part of the extension that still solves a specific problem. The choice should rest on needs visible in current work.

For example, Microsoft Lists and SharePoint let you create rules that send notifications about changes in a list or library. Configuring them needs the right permissions and is subject to the limits described. Such a feature can cover part of a custom extension; check its usefulness in the environment you use.

Compare the user's whole working day

In the example, what matters is whether the user gets the right message, can go to the case and knows what to do. The manager should see how they will spot a missing response after the change. If the current extension combined data from several places, the comparison must cover those dependencies too.

The new feature may need a different plan, different settings or a different way of granting access. Confirm these conditions with the administrator or the vendor. Set them against the work needed to maintain your own component: integration changes, problem handling and development. Keeping the existing code running needs its own justification.

Also look at the exceptions added over the years. Some may still matter; others may be left over from a finished project or a team change. The process owner should name the behaviours the company is choosing to give up. It is a chance to simplify the work, as long as the people involved understand the effects.

Switching off the add-on needs preparation too

Open cases may have actions scheduled in the current extension. Agree whether they will be finished there or taken over by the new feature. During the switch, avoid double messages and spot cases that ended up in neither flow. The company should know who clarifies such cases.

If the extension keeps its own history, decide where it will be available after the shutdown. The code and documentation can stay in the company's archive, even if the application stops running. Clean up access and connections within the agreed scope, with a person responsible for each environment.

After the change, support may be split differently: the product administrator takes over the configuration, and the contractor stays responsible for the integration that is kept. Write down this boundary and the rules for exporting data. Then a user knows where to report a problem, and the company can later change who looks after the remaining code.

Talk to Syntalith about an extension that now duplicates a product feature. We can discuss what it still does for the team and what scope of assessment will let you decide whether to simplify it, keep it or retire it. 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: a SaaS extension

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

  • When should you switch off a custom SaaS extension?

    When the vendor's new feature handles the same cases, including the agreements recorded in the extension, and the data and history have somewhere to go after the shutdown.

  • How do you check whether the vendor's feature is enough?

    On the same cases from the user's whole working day, counting the steps that still need workarounds and the data the new feature does not store.

  • 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.