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Company knowledge with sources: how the workflow works

Short answer

Permission-aware RAG checks access before the model sees a document: the search filters by the employee's groups, and PostgreSQL enforces the row access rule again. At Syntalith an AI application on company documents costs from €3,000 net. At 400 questions a month that each take 10 minutes of searching, it pays back in 1.5 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 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 · 3 min read

Example: the morning request inbox
Agent · ready

Statistics

AI knowledge bases: statistics 2026

1.5 mo.

payback of a €3,000 application at 400 questions a month: €2,327 of searching today, €355 with the application. Scenario.

Figures checked: 22 October 2026

The same company, two people, different access

An employee looks for the current leave procedure. The folder holds two versions, and some documents belong to HR alone. A manager from HR and a specialist from the warehouse ask the same question and should get different answers, each with sources that person can open.

The most common mistake when building such a search is hiding the citation only on screen. By then the model has read the closed document, and its content could shape the answer even if the link never appeared. The check has to run before the answer is generated, and the refusal has to read the same whether the closed document exists or not.

The path of a question through the system
  1. 01Identitythe employee's groups taken from the session, from one source of truth
  2. 02Searcha query limited to the documents of those groups
  3. 03Databasethe RLS policy in PostgreSQL checks every row again
  4. 04Versionan outdated document and conflicting sources are separate states
  5. 05Answeronly from passages that passed both checks, or a refusal

What it costs and when it pays back

Scenario: 400 questions a month
Today
400 questions × 10 min = 66.7 h (€2,327)
With the system, a person checks the output in 15% of the time
€349
Model, 1 call per case, Claude Sonnet 5.5
€6
Cost of one case
€5.82 today, €0.89 with the system
Saving
€1,972 a month

Payback of €3,000

1.5 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: 6,000 input tokens and 500 output tokens per call at Anthropic's rates, at the ECB rate of 1.1205 USD per euro on 22 October 2026.

The model is a small item here. The result depends on the time that searching and asking around takes today, and on how much of it remains for checking the answer.

Before we quote a build, we run a test on 20 to 100 questions the team has already asked: we compare the application's answer with what an employee found by hand, and we count the time from question to source. The test takes 5 working days and costs €0.

What our demonstrator showed

In the demonstrator, with 600 test documents and five fictional accounts, we checked 750 question and identity pairs: no answer or source went outside the asker's permissions. A separate test measured accuracy. Questions worded differently from the document found the right source at a rate of 0.511 across 45 pairs, because simple ranking recognises synonyms poorly. The lesson for a rollout: access control and search quality are two different tests, and the second needs a good embedding model chosen for the company's vocabulary. The mechanism is described in the PostgreSQL documentation: once RLS is on, a table with no policy returns no rows, but the table owner and roles with the BYPASSRLS attribute skip the rules. So the application connects to the database through a separate role without those rights.

A first trial in the company
  • One team and a controlled folder

    a test of 750 pairs on your groups

    5 working days

  • Questions in people's own words, and access removed after a role change

    accuracy and access results reported separately

    a decision on the build

  • Groups from the company's identity system, versions, document owners

    a search in the company's environment

    from €3,000

Where to start

Before a pilot, prepare documents with their owners and versions, the employees' groups and permissions, and a few dozen questions with the correct sources. Also check whether removing a permission changes the result from the very next question, as described in the article on a knowledge base after permission changes. The demonstrator's screens are on the page about company memory with permissions, and we run the build as part of AI applications.

For the first call, one question that keeps coming back to colleagues and a note on where the team looks for the answer are 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: answers from company documents

We run the same count for your documents in the free analysis.

€3,723

a month for finding answers to 800 questions in documents

Payback: 1 mo.

Our assumptions are 8 minutes to find an answer in documents or ask a colleague, and checking in 15% of the old time. €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 6,000 + 500 tokens per answer from documents, 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

  • What is permission-aware RAG?

    An AI search that checks which documents the asker may open before it prepares an answer. The model receives passages from those documents only, so a closed file does not even shape the wording of a refusal.

  • Is it enough to hide the source on screen?

    No. By then the model has read the closed document, and its content could reach the answer. The check has to run in the search and in the database, before the text reaches the model.

  • How much does such an AI knowledge base cost?

    At Syntalith an AI application on documents costs from €3,000 net, typically up to €7,000. At 400 questions a month of 10 minutes each, the payback is 1.5 months. Maintenance is priced per project.

  • What is RLS in PostgreSQL?

    Row-Level Security, a policy for access to rows. Once it is on, the database returns only the rows allowed for a given role, and a table with no policy returns nothing. The table owner and BYPASSRLS roles skip the rules, so the application uses a separate role.

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.