Skip to content

Blog · Published · Updated

Local AI for confidential proposals

Short answer

A local AI model suits confidential proposals when data rules rule out your current tool. The decision covers quality on your documents, user access, performance and responsibility for maintenance, and buying a server is only one of those elements. At Syntalith an app on a local model costs from €3,000 net plus GPU hardware. With 40 proposals a month at 120 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
model on your server or in the cloud in the EU
quoted after the review
same work in application with EU cloud model
from €3,000
task, data and equipment analysis
€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

Confidential data and AI: statistics 2026

1.7 mo.

payback of a €3,000 local app at 40 proposals a month: €2,792 of work today, €1,052 with checking and a GPU server. Scenario.

Figures checked: 22 October 2026

Establish what your data rules forbid

An industrial proposal contains the client's drawings, supplier terms, your own costing and a description of an unannounced project. The team wants to compare requirements faster or prepare a draft reply, and has no permission to put the material into the chat tool it uses.

„Data must not leave the company” can mean a ban on public tools, a required region or full isolation from the network. These are different conditions. The person responsible for security and for the client contract confirms which one applies. The location of the model does not describe the whole flow: material also ends up in logs, backups, the document-reading tool and the support system. A label saying „on-premise” does not confirm compliance with the contract.

OptionWhat to settle
An approved APIprocessing terms, features and data restrictions
A private cloud environmentlocation, access control, maintenance and dependencies
Your own infrastructurequality on the task, capacity, updates and support
Narrow the task before choosing a model
  1. 01Resulta summary of the proposal's requirements with the source shown
  2. 02Controlwhat the salesperson checks and what the engineer checks
  3. 03Trialtables, scanned pages, unclear requirements and long material
  4. 04No basisthe system reveals a gap instead of adding a commitment
  5. 05Loadone person working, and several people at once

What a local model for confidential proposals costs and when it pays back

Scenario: 40 proposals a month
Today
40 proposals × 120 min = 80 h × €34.90 = €2,792
With the app, an employee checks the output in 30% of the time
€838
Hetzner GEX45 GPU server
€214
Saving
€1,740 a month

Payback of €3,000

1.7 months

The volume, the time and the checking share are the scenario's assumptions, which we measure in the trial. €34.90 an hour is the EU average hourly labour cost for 2025 according to Eurostat. Price of the GEX45 with 24 GB of GPU memory from Hetzner's website on 22 October 2026, without the one-off setup fee of €209.

The count covers the time spent searching, reading and compiling the material. What stays is the time to check the output against the source, 30% of today's work in the scenario. We measure both times in a trial on 20 to 100 cases the team has already handled. We leave 30% of today's work for checking because a salesperson or an engineer reads every commitment in a proposal.

What runs locally and what needs agreeing

In a commercial proposal, an unconfirmed commitment weighs more than a few seconds of response time. So the trial covers situations with no correct answer: the system has to reveal that there is no basis. A trial on one laptop assesses a single task, and readiness for a department needs a load check with several people at once. If the main difficulty is finding the current version of a proposal, you also need a knowledge base with versions, because the model alone does not know which document applies.

What to agree with IT beyond the model
  • Where the app takes documents from and where it saves results
  • What stays in logs, backups and the history of questions
  • Who has access to questions, answers and summaries
  • Who updates the model, the app and the set of documents

Who is responsible for running it

Name the owner of the infrastructure, updates, access and user tickets. Ask who will check quality after a model change and what happens during an outage. A small local model may be enough for narrow work, and you should not assume it will be better or cheaper than every outside service. A study discussed by IBM shows that companies choose models for cost, security and fit. It is a vendor's study and does not point to a solution for your company's documents.

An API, a private cloud or your own server
  • The contract allows processing by a provider

    an approved API with data terms

    licence and tokens

  • A required region and access control

    a private cloud environment

    priced after the review

  • The material may not leave the company

    a local model with an app for proposals

    from €3,000 plus hardware

Where to start

For the first call, prepare a description of the confidentiality requirements, the type of documents and the number of people who would use the solution. We compare the whole period of use: preparation, hardware, maintenance, changes and checking work. We roll out local models as part of private LLMs, and we build the view for working with sources as an AI app. For the free process review, a description of one case and the places where the material sits is enough. Confidential files stay in the company, and you get a written plan within 2 working days.

Worked example · Scenario

How we count the payback: preparing proposals

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

€2,094

a month for preparing 120 quotes from customer enquiries by hand

Payback: 1.7 mo.

30 minutes per quote from an enquiry 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 4,000 + 1,500 tokens per draft quote, at the ECB rate of 1.1205 USD per euro on 22 October 2026. The extra margin is a scenario: we assume that 1 in 40 enquiries quoted the same day ends in an order that a slow reply loses today, with a margin of €344. 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 ↗

A model on your server or in the cloud in the EU, proven on your tasks.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 →

Private AI models

A model on your server or in the cloud in the EU, proven on your tasks.

We select the model and equipment for the task, run it and measure the quality using your examples before you buy anything. The data stays in the company or in the cloud in the EU. We price implementation, hardware or hosting and support separately after analysis.

View private AI models →
model on your server or in the cloud in the EU
quoted after the review
same work in application with EU cloud model
from €3,000
task, data and equipment analysis
€0

Questions

  • Is a local AI model suitable for confidential proposals?

    Yes, when data rules rule out an outside service and a trial on your proposals shows enough quality. Before you buy, settle which confidentiality condition applies: a ban on public tools, a required region or full isolation from the network.

  • Is a local model cheaper than an API?

    Not always. What counts is the whole period of use: hardware or hosting, administration, updates and the time spent checking results. With few proposals, an API in an approved environment can be cheaper.

  • How much does such an app on a local model cost?

    At Syntalith from €3,000 net plus GPU hardware, for example a Hetzner GEX45 server with 24 GB at €214 a month. With 40 proposals a month, the payback is 1.7 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.