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Contract changes: when to customize a model to categorize them

Short answer

Comparing contract versions marks the changes, and an AI model can give them categories so the coordinator knows whom to pass each difference to. The frequency of a report is a substantive change, and a new paragraph break is formatting. In a scenario of 600 contract changes a month, agreed category definitions cut errors from 20% to 8%, and fine-tuning to 4%, which together save 8 hours of corrections, or €279 a month.

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  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
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Statistics

Contracts and AI: statistics 2026

8 h

fewer corrections a month at 600 contract changes: agreed category definitions cut errors from 20% to 8%, fine-tuning to 4%, at 5 min per correction. Scenario.

Figures checked: 22 October 2026

A highlighted difference and its place in the review

A client sends a contract back after edits. The version for agreement says „Report delivered monthly”, and the version after comments says „Report delivered weekly”. Elsewhere only the line breaks of a paragraph changed. The comparison marks both places, and the coordinator has to decide whom to pass each of them to.

The model gives the first change the category of reporting obligations, and the second the category of formatting changes. The coordinator sees both passages side by side, checks the category and sends the substantive change to the right reviewer, without passing on the whole list. When the meaning of the new wording depends on a cross-reference to another clause, the category stays unresolved, and the view lets you go back to the documents.

A contract change for review
  1. 01Versionsthe document for agreement and the one after the client's comments
  2. 02Differenceboth passages side by side
  3. 03Categorysubstantive, reporting, formatting
  4. 04Reviewerfrom the list of who is responsible for each category
  5. 05Unresolvedback to the documents when there are cross-references

What a simpler change gives, and what training adds

Scenario: 600 contract changes a month
Today: 20% errors × 600 × 5 min
10 h (€349)
After a change without training (agreed category definitions): 8%
4 h (€140)
After fine-tuning: 4%
2 h (€70)
The simpler change saves 6 h, fine-tuning adds 2 h (€70) a month

Compare fine-tuning with the cost of examples, training and a new evaluation

The error shares and the correction time are the scenario's assumptions, which we measure on the client's cases not used for training. €34.90 an hour is the EU average hourly labour cost for 2025 according to Eurostat.

In this count, agreed category definitions give most of the effect for a fraction of the cost. Training makes sense at a larger scale or when the remaining errors are expensive. We keep the meaning of a category apart from the reviewer's name: a change of responsibilities in the team needs an updated assignment, with no retraining of the model.

A comparison before deciding on training
  • Evaluation cases kept apart from training examples
  • The same set for the current model, the simpler change and the adapted model
  • Correct answers prepared by the people who correct the results today
  • Errors counted separately for each kind of mistake
  • A plan for a new evaluation after a change of base model or process

The set of training examples has to be maintained: when the process, the naming or the base model changes, the evaluation is repeated on the same test set. We put that cost in the quote together with the training itself.

Start with text comparison

If the team mainly needs to find the changed places, start with the tool you have: Microsoft Word compares two documents and shows the differences in a third document. Contract management systems also compare clauses semantically, as the Conga documentation describes. Categorising is separate work, needed when there are many marked passages and the team sorts them by the same topics. Before adaptation, the company's experts agree what „an editorial change” means, because for one person it is the layout of the text, and for another also a new wording.

Editor, ready model or fine-tuning
  • You only need to find the changes

    comparison in the editor

    no AI

  • Many changes, clearly defined categories

    a ready model with category definitions

    an app from €3,000

  • The model confuses the same categories despite the definitions

    fine-tuning on pairs scored by experts

    priced after the comparison

What to discuss before fine-tuning for contract changes

Fine-tuning needs changes between two versions with a category confirmed by an expert; an „accepted” comment from old negotiations does not explain the kind of change. We run the comparison on pairs of versions not used for adaptation. The scope of the contract workflow is described on the AI for contracts page. We adapt models as part of our private LLMs, and we build the app where an employee sees the result next to its source as part of our AI apps. For the free analysis, a few examples of an error that keeps coming back and a note of who corrects it today are enough.

Worked example · Scenario

How we count the payback: contract review

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

€2,094

a month for checking 80 contracts by hand

Payback: 1.7 mo.

45 minutes to compare a contract with the template and list the differences 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 30,000 + 2,000 tokens per comparison of a contract with the template, 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 ↗

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

  • How does AI help review changes in a contract?

    It gives the marked changes categories, for example substantive or formatting, and shows both passages side by side. The coordinator sends each change to the right reviewer.

  • When does fine-tuning for contract changes make sense?

    When a ready model keeps confusing the same categories despite clear definitions, and experts have confirmed categories on pairs of versions. Comments from old negotiations alone are not enough.

  • How much does fine-tuning a model cost?

    An AI app at Syntalith costs from €3,000 net, and we price model adaptation after comparing it with a simpler change on cases the model has not seen. In the scenario, fine-tuning adds 2 hours a month beyond what agreed category definitions give.

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.