We walk into the operation, find the work that eats hours and salaries, and close it with agents. We count the result in money: 1 to 5 weeks, and the before and after in one table.
We pull calls from Bitrix24, MTS, MegaFon, and Rostelecom, merge duplicates, transcribe them, and run them through the sales lead’s checklist: script, objections, next step. In the morning the manager has a report on every rep.
1,300+
calls in a two week report
100%
of conversations scored
02
Listings
Listing generator for marketplaces
Wildberries and Ozon: photo, graphics, copy
The seller uploads a photo and the specs. The system renders on-brand graphics, writes the SEO description against search demand, and checks the platform limits. A listing is ready in minutes.
20 min
per listing, instead of three days
×8
more listings a week
03
Organic
From zero to hundreds of thousands of visits
Search trends, pages, traffic
The system watches search trends in the niche, proposes pages, the model writes, and an editor hits ok. In a year the site went from zero to 450,000 unique visitors a month with no ad budget.
0 → 450k
uniques a month in a year
$0
spent on paid traffic
04
Engineering
An agent pipeline for the product
The team asks, agents change the code, people check
Anyone writes in chat what they want changed. An agent breaks the task down, edits the code, runs the tests, and comes back for review. Three people shipped 15 commits a month. One developer with agents now ships 383.
15 → 383
commits a month
−66%
engineering headcount
05
Influencers
Trends and the first message to creators
Instagram, TikTok, YouTube: a sheet and a first touch
An agent catches trends in the niche, finds creators they land with, collects contacts and reach, and writes the first message. Fifteen people doing the search by hand became three who only negotiate.
15 → 3
people on the search
−75%
sourcing budget
06
Reviews
Marketplace reviews, under control
Ozon, Wildberries, Google Play
The model sorts reviews by topic, catches the negative ones, and answers in the brand’s voice. The reply can recommend a product. On Mondays management gets a digest of what is actually annoying customers.
100%
of reviews handled
<30 min
average reply to a complaint
07
EdTech
Lesson video without a crew
OkiTalki: lessons without a studio
For a language app we built a line for lesson video: a script from the method, voice, a teacher avatar, edit, and subtitles in three languages. A lesson clip takes an hour.
×40
faster: an hour instead of a week
3 languages
from one script
08
Small business
The books in one chat
Telegram: tasks, money, clients, by voice
The owner dictates what used to live in their head: tasks, payments, what was promised. The bot keeps the books, reminds, builds the weekly report, and answers what May earned.
1 chat
instead of three tools
$0
of CRM subscriptions
03 / Who does the work
Two partners, from the first call to production
From the first call through production. No account manager who has to be briefed before they can speak.
01
Stanislav Kuznetsov
Partner, systems
Operations for an international e-commerce company: a team of 15+ across five time zones, production ×2, revenue ×4.
More than ten years in operations, from a hospital to e-commerce. A certified business analyst.
Runs his own businesses on an AI team: an EdTech product, tools for marketplace sellers, a content factory.
Lives in Buenos Aires. Russian is native. English and Spanish are working languages, so a call can run in any of the three.
Studied at the State University of Management. An external auditor of ISO 9000 since 2002 (VNIIS), then a business trainer and coach, and an EFQM assessor since 2007.
In 2021 and 2022 he added Machine Learning at Stanford Online and AI For Everyone at DeepLearning.AI. In B2B he looks for money lost when work passes between people: technology scouting, market outreach, and the selection funnel.
We do not sell "an AI implementation". We can see where it will return real money, and we build that ourselves. If there is no such place, we say so on the first call.
04 / How we work
Four steps. The first one is free.
No month-long diagnosis, and no specification that has to be signed before anyone builds.
01
Look 30 minutes
A call: what hurts, where the money leaks, what to automate first. If AI is the wrong tool, we say so.
02
Prototype 1–2 weeks
A working version on your data. Not slides. Something you can already use.
03
Launch 2–3 weeks
We fit it into your process, teach the team, and turn on monitoring and reports.
04
Keep subscription
We tighten accuracy, add scenarios, and send the numbers once a week.
05 / Money and shape
The frame is clear before the first call
Price and result are fixed before we start, not after we have had a look at you.
about $2,500
A pilot on one process
Price and result are fixed before the start. A prototype on your data in the first one to two weeks.
before we start
Payback, counted up front
Before launch we estimate what it returns and when. If the economics do not work, we decline and say why.
subscription
After launch
We tighten accuracy, add scenarios, and send a weekly note: what shipped, and which numbers moved.
06 / Rules
The filter runs both ways
We do not take every request that contains the word "neural".
01
We will say no if AI is the wrong tool
If the job is ordinary automation, a hire, or a process fix, we say that. We do not sell the technology for its own sake.
02
P&L first, stack second
We take it when we can see a path to revenue, savings, or team capacity. "Build a bot" is not a task. "Support is drowning, we need twice the volume without a hire" is.
03
Two partners on the work
On the call, in the thread, and in the system, you are talking to us. If we do not understand the business, we ask.
04
Weeks, not months
We do not run the cycle of specification, mockups, approval, then build. In two to four weeks the system is running.
05
Numbers every week
A short report: what shipped, which metrics, what is next. If something goes wrong, you hear it then.
07 / Questions
What people ask before they write
Straight answers.
What does it cost?+−
A pilot is about $2,500. Price and result are fixed before we start. We count payback before launch. If the economics do not work, we decline.
An agency, or two people?+−
Two partners, and agents. On the call, in the thread, and in the system, you are talking to us.
Why you, if we could hire?+−
A hire is months of search, a salary, and the risk that the person cannot do it. We hand over something running in two to four weeks, then support on a subscription. If a hire is the right answer, we say so.
Models invent things. Can this run in production?+−
We do not promise perfect accuracy. We measure: regression scenarios, a staged launch, a weekly report with numbers. Where the model is unreliable, it does not sit on a critical step.
How fast is a result?+−
A prototype on your data in the first one to two weeks. Launch in two to four weeks.
What if it does not work?+−
We start with a free 30 minute look. We take the work only when we can see a path to money. After that, weekly reports: if it is going wrong, you hear it then.
08 / Next
Small teams with AI will eat large teams without it.
In 30 minutes we will say what that means for your business, and which process to start with. One call, and it is clear whether we have something to offer.
Denis or Stanislav. We answer ourselves within a day.
We have it.
We will write or call back. If it is faster, open Telegram.
