Legal department · contract review

The contract went out for signature with a stranger's edit in clause 7.3. Who caught it?

The counterparty sent back "your own template with cosmetic edits." Your lawyer read it at the end of the day, the eighteenth document in a row. A mutual penalty quietly became one-sided, the payment term slipped from 10 days to 45 — and the signature is already on its way. AI contract review checks the incoming text against your reference template in 2 minutes and flags every deviation, risk, and deadline. Start with a free automation map: in 14 days we'll show where your contract flow is leaking, and what it's costing you in hard currency.

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2 minutes: to review a contract instead of an hour
100%: of contracts checked against your template
0 ₽ · 14 days: automation map for the legal function

Legal department · contract review — AI implementation diagram

01Sound familiar?

Recognize your own contract flow?

Friday, 5:40 PM. The sales director messages: "needs to be signed off today, the client's waiting." A 46-page contract, one lawyer, four more of the same waiting behind it. He skims it, looking for familiar wording — and signs off on something that looks like your template. Looks like.

The incoming file had nine deviations from the reference. Eight were harmless. The ninth was the liability clause, where your damages cap quietly disappeared. That surfaces six months later, when a claim comes in for a sum that never existed in your risk model.

And at companies without an in-house lawyer, it's simpler and worse: the owner or the accountant reads the contract between two other tasks. An outside lawyer charges from 5,000 ₽ per document and replies in two days — so small contracts don't get checked by anyone. People just sign and hope.

02The cost of inaction

What you're losing while you read this page

Better to run the numbers on your own figures. One missed clause costs more than a year of proofreading budget. Plug in: how many contracts pass through you per day, what share go out for signature without a proper review, and your average contract value.

Inquiries per day 30

Lost before response 50%

Average deal size 70,000 ₽

Lost revenue per month — per year — —

A rough estimate based on your inputs — we calculate the exact numbers in a free consultation.

Get this money back

03How it will be

Your Monday, a month after implementation

A contract from a counterparty lands in the inbox at 10:10 PM on Sunday. By Monday it's already broken down: the AI checked the text against your reference, flagged nine deviations, marked three of them red — a one-sided penalty, a 45-day payment delay instead of 10, a vague acceptance clause. Each flag comes with a quote, a link to your template, and a suggested edit. The lawyer opens the document and works with three disputed paragraphs, not 46 pages: fifteen minutes instead of an hour. You open the summary and see that 62 contracts went through this week, not one went out for signature without a check, and two counterparties keep editing the same clause — now you know exactly what to raise with them.

Now

Reviewing one contract40–60 minutes of reading, skimmed by evening

Checking against your templateBy eye and memory, not every deviation gets caught

Small contractsSigned without a lawyer — "it's standard anyway"

Risk visibilityThe claim arrives before anyone understands what went wrong

With AI

Reviewing one contract2 minutes to break down, 15 minutes of lawyer time on the disputed part

Checking against your templateEvery deviation from the reference, with a quote and a link to the clause

Small contractsGet the same check as large ones — all 100%

Risk visibilityA log of which clauses get edited most, and by whom

04How it works

Three steps, and you don't write a single line of code

01 · Step 1 · 14 days · 0 ₽
We break down your contract flow
We look at the numbers, not the vibe: how many contracts pass through per month, which types, how much time proofreading takes, what's already gone wrong because of a missed clause. We take your reference templates and rules: what's a red line for you, what's up for negotiation. The output is a document showing where the flow leaks, what to fix first, and what it's costing you in hard currency.
02 · Step 2 · pilot from 90,000 ₽
Pilot on one contract type
We take your highest-volume type — supply, services, lease — and train the AI on your templates and your lawyer's positions. It finds deviations from the reference, risks, deadlines, amounts, penalties, auto-renewal, jurisdiction, and delivers a report with quotes. We measure it on real documents: how much time it took before and after, what the AI caught that a human missed. You set the success metric yourself.
03 · Step 3 · scale and ongoing support
We roll it out across the whole flow
We connect the remaining contract types and intake channels: email, document management system, shared folder, chat. We add contract drafting from your template using deal data, and a log of counterparty edits. From there, we keep running it: retraining on new cases, updating rules as the law and your practice change, and tracking the metrics.

05Proof

How a law firm stopped operating blind

Edemium case study · law firm

A law firm, 5+ years in the personal bankruptcy market. 40 employees, 8 of them in the call center. Ad budget — 2M ₽ per month.

This is an adjacent problem — not contract review, but the flow of inbound inquiries. But the failure mode was the same species: more documents and calls than a human can physically process, and the manager running on gut feel instead of facts. 60% of leads died before the first call — 480,000 ₽ thrown away every month. Only 12–15% made it to payment.

The manager didn't believe AI could handle the specifics of Russia's 127-FZ bankruptcy law and the legal terminology. He agreed to a 2-week pilot — just to see.

The AI layer started greeting every inquiry within 30 seconds, collecting the data, and handing the lawyer a ready-made card. All channels were consolidated into one CRM, and AI began reviewing every manager's call — the entire flow, not a sample.

Within a few weeks, paid conversion rose from 15% to 35%, lead loss dropped from 60% to 15%, and revenue grew by 3M ₽ a month on the same ad spend. The same principle works on contracts: the machine reads 100% of the documents, the human decides on what's actually disputed.

"I used to have no idea where the money was leaking. Now I check the summary for five minutes in the morning — and I know everything about the department."

This is a real case; client name withheld under NDA. Full metrics schedule available on request.

I want the same result

06While you're thinking it over

A missed clause can't be fixed after the fact

The contract you signed yesterday is already in force — with every edit nobody caught. A one-sided penalty, a payment delay, a year-long auto-renewal, jurisdiction in someone else's region: this isn't a mistake you can roll back, it's an obligation. It won't surface today — it'll surface six months from now, when a dispute starts, and the stakes will be counted not in a lawyer's hours but in the amount of the claim. While your lawyer skims the eighteenth contract of the day, every next signature is a bet on his attention span at 5:40 PM on a Friday.

07We know what you're thinking

Honest answers to the main doubts

We can't hand our contracts to someone else's neural network

Right you shouldn't. The setup is built so documents stay inside your perimeter: on your own server or in a closed environment, with no training on your data. Access is role-based, and every request to a document is logged. We sign an NDA before the first call, and the exact storage architecture gets fixed in the automation map — before you upload a single file.

We have our own specifics and our own wording, AI won't handle it

The AI doesn't show up with some generic "common law" playbook. It's trained on your reference templates, your editorial position, and your list of unacceptable terms: what's a red line for you, what's up for negotiation. During the pilot, we run it against contracts you've already signed and check the results against your lawyer's judgment. If it doesn't match, we retrain it before the system goes live.

What if the AI misses a risk — who's on the hook?

The decision and the signature stay with the lawyer; the AI doesn't replace him. It does the first pass through 100% of the documents and delivers a report with quotes and links to the relevant clauses — so a human reads three disputed paragraphs, not 46 pages. Right now the alternative isn't "flawless proofreading," it's a skim at the end of the day.

This is too expensive for our volume

An hour of lawyer time costs 2,000–5,000 ₽, and an outside contract review starts from 5,000 ₽. Thirty contracts a month at an hour each is 60,000–150,000 ₽ of time — and that's before the cost of a single missed clause. The pilot, from 90,000 ₽, pays back in 2–4 months. On the automation map, we'll show the math on your own numbers before you pay a ruble.

We don't have the people to implement this

You don't write a single line of code and you don't hire developers. We need your reference templates, access to the folder or inbox where contracts land, and about 40 minutes of your lawyer's time up front to walk through the red lines. We handle the rest turnkey.

✓

A pilot with no risk for you

We launch the pilot in 2 weeks. You set the success metric yourself. Don't see the result on it — we refund the pilot. The risk is ours, not yours.

08Pricing

What's cheaper — AI or one more lawyer

A lawyer on proofreading: ~1.8M ₽/year salary + taxes, reviews 8 contracts a day, skims by Friday evening AI layer: pays back in 2–4 months, reviews 100% of contracts in 2 minutes each, no weekends, no fatigue

Consultation

0 ₽Process breakdown + payback calculation

Funnel breakdown and loss points
Lost revenue calculated in hard currency
An honest verdict: where AI will pay off

Get it for free

StartScenario pilot

from 90,000 ₽2–4 month payback

One contract type: checked against your reference, risks, deadlines, amounts, penalties
Trained on your templates and your lawyer's editorial position
Measured on real documents: time before and after, what was found

Launch a pilot

Turnkey

Custom quoteFull stack + ongoing support

All contract types and intake channels: email, document management system, shared folder, chat
Contract drafting from your template using deal data
Log of counterparty edits + ongoing support and retraining

Discuss your project

09Frequently asked questions

Be the first whose contracts never go out for signature unread

AI for the legal function in Russia is still an opening, not a standard. While competitors skim counterparty edits at the end of the day, you can review 100% of your documents in 2 minutes each and know exactly which clauses people keep trying to rewrite on you. In a year, everyone will have this — the head start goes to whoever starts today, before a missed clause turns into a claim.

I want to be first in my industry

10Connection point

Find out where your contract flow is leaking — free, in 14 days

We take on a limited number of projects a month so we can run each one personally. Leave a request — we'll get back with an automation map: how much time proofreading takes, which risks slip through, and what it's costing you in hard currency. We sign an NDA before the first call.

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