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Company Brain AI: Ready Platform or Custom System?

Short answer

A ready platform wins when knowledge lives in one ecosystem, for example Microsoft 365 or Confluence, and the questions concern that content. Your own knowledge base wins with many sources, strict permissions or data that may not leave the company. For 120 people over 24 months, licences at $21 cost €53,976, and your own system from €3,000 with the model costs €4,748, before maintenance, which we price per project.

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 platforms: statistics 2026

€49,228

difference over 24 months for 120 people: licences at $21 a month against your own knowledge base with the model, without maintenance, which we price per project. For 25 people the difference is €7,881. Scenario.

Figures checked: 22 October 2026

A map of ready platforms in 2026

ToolFor whomPricing modelWhen it wins
Microsoft 365 Copilotcompanies on Microsoft 365$21 per user a month on the Business planknowledge in SharePoint, Teams and Outlook
Google Gemini Enterprisecompanies on Google Workspaceper-user editions published by Googledocuments, email and drives in Google
Atlassian Rovoteams in Jira and Confluencein paid Cloud plans, 25 to 150 credits per personproduct knowledge in Confluence, tickets in Jira
Onyxcompanies with their own ITopen source, MIT licence, you pay for the server and upkeepdata may not leave your infrastructure
Your own knowledge basemany sources, strict permissionsfrom €3,000 for the build, upkeep, modelsources from different systems and an answer with a quotation

Sources of the descriptions: Microsoft, Google and the Gemini Enterprise editions, Atlassian, Onyx.

Since 5 May 2026, Microsoft has offered federated connectors that fetch data from other systems over MCP at the moment of the question, with the user's permissions and a link to the source. That narrows the advantage of your own systems for popular SaaS apps. The advantage stays where the source is an internal system, a folder on a server or a database with access rules no ready connector knows.

Which option for which situation
  • Knowledge in one ecosystem, questions about that content

    that ecosystem's ready platform

    a per-user licence

  • Data may not leave the company, you have your own IT

    Onyx or your own system on the company's server

    server and upkeep

  • Many sources, internal systems, strict permissions

    your own knowledge base with quotations from the source

    from €3,000

What an AI platform or a custom knowledge base costs on your numbers

Scenario: 120 people over 24 months
Platform: 120 × $21 × 24 months
$60,480 (€53,976)
Your own system: build from €3,000
Model: 120 × 40 questions × 24 months, Claude Sonnet 5.5
€1,748
Your own system in total
€4,748

A difference of €49,228 over 24 months; for 25 people €7,881

The number of people, the questions and the horizon are the scenario's assumptions, Maintenance is priced per project, so the scenario leaves it out. The Copilot Business rate with an annual commitment is Microsoft's, with a promotion of $18 in the first year until 31 December 2026. Model: 6,000 input tokens and 500 output tokens per question at Anthropic's rates; dollar amounts converted at the ECB rate of 1.1205 USD per euro on 22 October 2026. Copilot also does things beyond answering from documents, so the comparison concerns that function only.

Two items are easy to miss on the build side: tidying the documents before the start, and the time of the person who approves changes to the sources. On the platform side it is easy to miss that the number of users grows and the rate rarely falls. According to the European Commission (2026), 42% of EU SMEs and mid-caps already use AI, mostly in a limited and experimental way, so seats that nobody uses are a real risk.

When your own knowledge base wins

Signs that a platform is not enough
  • An answer needs sources from three or more systems, internal ones included
  • HR, finance or the board hold documents others may not see, even in part
  • Data has to stay in your infrastructure or in a chosen region
  • The answer has to quote a specific version of a procedure and its approval date
  • The team asks questions in its own words, and keyword search fails

You can measure retrieval quality before you buy. According to Anthropic (2024), combining contextual embeddings with BM25 search cut failed retrievals by 49%, and by 67% with reranking (Contextual Retrieval). Run the same test on the platform and on a prototype of your own system: 50 questions the team has already asked, and the source that should appear.

What to ask a supplier for before you sign

Ask for a test on your own questions, in place of a presentation. Ask what happens to an answer after an employee loses access to a folder, how long the index remembers a deleted document, and whether the answer shows the version of the source. We ask ourselves the same questions when we build, as the post about a knowledge base after permissions change describes.

We build your own knowledge base as part of our AI apps, from €3,000 net. If the test shows that a ready platform is enough, we will say so in the free analysis, and a Copilot rollout for the team helps you put it in place.

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

  • A ready platform or your own knowledge base?

    A platform when documents, email and tasks sit in one ecosystem and its connectors are enough. Your own system when there are many sources, permissions have to apply to every search, or data may not leave the company.

  • How much does a ready knowledge platform cost?

    Microsoft 365 Copilot Business costs $21 per user a month with an annual commitment. For 120 people over 24 months that is $60,480, or €53,976. Rovo is included in paid Cloud plans of Jira and Confluence, with a credit limit.

  • How much does your own AI knowledge base cost?

    At Syntalith from €3,000 net for the build, plus maintenance, which we price per project, and the model cost by question. For 120 people and 40 questions per person a month, the scenario comes to €4,748 over 24 months.

  • Is Onyx free?

    The Community edition has an MIT licence, so the licence costs nothing. You pay for the server, updates, connectors and the time of the person who maintains it.

  • When is a platform cheaper?

    With a small team. For 25 people, licences cost €11,245 over 24 months and your own system €8,812, so the difference stops justifying a build if the platform covers your sources.

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.