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Custom employee improvement idea software

Short answer

A custom app for improvement ideas links an employee's proposal to the decision to test it and to the trial result, which later teams can see. When a similar idea comes back from another plant, the manager sees what has already been learned. With a few ideas a month, a list with rules in your current tool is enough.

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

Improvements and AI: statistics 2026

1.8 mo.

payback of €3,000 at 200 ideas a month: €2,327 of work today, €700 with checking and the model. Scenario.

Figures checked: 22 October 2026

An idea from submission to result
  1. 01Proposalthe problem and the idea in the employee's words
  2. 02Decisionwho tests the idea and to what extent
  3. 03Triallimited, with a person in charge
  4. 04Resultwhat worked, what did not and why
  5. 05Returna similar idea shows the earlier trial

The idea comes back, and the result of the earlier trial is lost

Say an employee proposes moving where packing materials are stored. A similar idea was tested earlier at another plant. The coordinator remembers the conversation, but the result stayed in a presentation and the manager's emails. The new author does not know whether the proposal was rejected or simply never picked up.

In the proposed app, the coordinator can link both submissions and find the description of the earlier trial. The person responsible for the area decides whether the result can be used or whether local conditions need a separate test. The idea shows the agreed scope of the trial, the person in charge of it and the later conclusion. The author sees what is happening with the proposal and why a decision was taken.

A result can mean a rollout, a need for more work or dropping the idea. What matters is that the next team can understand the reason. A “closed” tag on its own says little about whether the idea was useless or the problem was solved another way. The company sets who assesses proposals and on what basis they decide on further action.

This story also shows the limit of the app. A description of the earlier trial helps the conversation, and it does not settle that the change will suit another place. Assessing the way of working and approving a trial belong to the people responsible. The tool organises the knowledge and who looks after each idea.

Start with how employee improvement ideas are handled

If there are few submissions, a shared list and a regular review may be enough. Microsoft Lists and SharePoint offer rules that notify people of changes to a list or library, with the right permissions and the limits described there. It is a feature to check when the problem is that nobody hears what happened to a submission.

You can also compare a ready idea management system with the project tool the company already uses. What counts is whether the author can submit a proposal easily, the coordinator can spot similar ideas and the area owner can take over the agreed trial. Include employees who use it only occasionally, and how they get access.

An integration makes sense if the idea list works well, but the chosen trials are run elsewhere and the result never gets back to the author. Your own workflow is worth considering when the company wants to link proposals from several places, shared decisions and the use of results consistently. The purchase should cover this need, without automatically replacing the management of all projects.

Optional AI can help find similar descriptions. The coordinator should check whether they really concern the same problem. The app can also work with ordinary search and manual linking of proposals.

Keep the result that will be useful later

When moving data, the most important items are ideas waiting for a decision, trials in progress and results the team may come back to. Old submissions without a decision need the process owner's assessment. The import alone should not present them as still-current commitments.

Agree who supports the authors and who looks after the connections to project tools. The export should keep the links between the proposal, the trial and the result. Access to the data, the code and the documentation lets you change supplier later without losing the teams' work.

Talk to Syntalith about an idea that came back despite an earlier trial. We can discuss where the information about the result should live and what scope of connection or app will help you use it. The pricing rules are on the pricing page.

What an improvement ideas app costs and when it pays back

Scenario: 200 ideas a month
Today
200 ideas × 20 min = 66.7 h × €34.90 = €2,327
With the system, a person checks the output in 30% of the time
€698
Model, 1 call per case, Claude Sonnet 5.5
€2
Cost of one case
€11.63 today, €3.50 with the system
Saving
€1,627 a month

Payback of €3,000

1.8 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, converted at the ECB rate of 1.1205 USD per euro.

What we measure in the trial
  • Time from receiving a case to the result, before and after the change
  • Cases the app passed to a person
  • Corrections by the person checking
  • Model and maintenance cost at the target volume

Where to start

In the free process review we choose one process and count the team's volume and working time, and within 2 working days you get a written summary with a price. We build as part of AI apps, and we price maintenance separately.

Worked example · Scenario

How we count the payback: improvement ideas

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

€5,235

a month for quoting 150 enquiries by hand

Payback: 0.7 mo.

1 hour to quote an enquiry with a drawing 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 enquiry in our quoting system (about €0.0008) plus pricing the lines (Claude Sonnet 5.5, about 4,000 + 1,500 tokens), at the ECB rate of 1.1205 USD per euro on 22 October 2026. The extra margin is a scenario: we assume 1 in 40 enquiries quoted the same day ends in an order that a slow reply loses today, with a margin of €688. In the review we count it on your sales process.

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

  • Why use an app for improvement ideas?

    So that the proposal, the decision to trial it and the result sit in one place. The next team with a similar idea sees what has already been tested and what was learned.

  • Is a SharePoint list enough?

    With a few ideas a month, yes, with rules that automate notifications. An app makes sense when ideas come from many plants and trial results get lost.

  • How much does it cost?

    At Syntalith apps, automations and AI agents start from €3,000 net. At 200 ideas a month of 20 minutes each, the payback is 1.8 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.