AI business process optimization
A day of work gets done overnight
We take over the routine your team repeats every day by the same rules: data collection, inbound requests, documents, reports.
From our practice
22,000+
job posts gone through in one run
268,000+
followers without a single new shoot
almost600,000
export rows turned into a report with conclusions
What we count as a result
Hours given back to the employee
Errors that no longer happen
Work that runs overnight and is ready by morning
12 tasks we have already taken off teams
All examples are anonymised: no company names and no details of the solutions.
Sales and clients
22,000+
job posts gone through in one run
Collecting and checking company information
How it works
How it is done today
For every company someone opens a dozen tabs: the website, registries, directories, job boards. Then copies it into a spreadsheet by hand. Ten to fifteen minutes per record, and by the end of the day attention is gone.
What the system does
- Finds companies by your criteria on its own: industry, region, size, activity
- Fills in the card: website, company details, phone and email, head, industry, revenue
- Filters out what does not fit by your own rules and removes duplicates
- Every day it hands over only what is new - what was not there yesterday
- Next to every record it notes why it got there and where each field came from
What it gives you
- A day of work gets done overnight
- Every field has a source you can check
- People spend their time on conversations, not on searching
From practice
A recruitment company: the system tops up their working database on its own every day. How right it is was tested on their own data - we compared its picks with the people the team actually took on. In another project a single run went through more than 22,000 job posts.
Sales and clients
77
open channels under watch around the clock
Sorting inbound requests
How it works
How it is done today
A stream of messages in chats, email and messengers. Someone reads everything, some of it gets lost, and the important request surfaces a week later, when the person has already bought elsewhere.
What the system does
- Reads the stream and separates real requests from noise, ads and idle talk
- Understands what the person is writing about and how ready they are to talk
- Puts together a short brief: who this is, what they do, what exactly they need
- Under every conclusion it quotes the person's own message - you see where it came from
- Notifies the owner and suggests options for the first reply
What it gives you
- Sorting runs around the clock, nothing gets lost
- The manager works with a shortlist instead of reading everything
- Sorting one request costs less than two roubles
From practice
A company that sells services to other businesses. 77 open channels under watch. What is not needed is filtered out before the expensive processing - that cut costs almost in half. The manager gets a simple screen: a queue, "take it" or "not a fit", a ready reply.
Sales and clients
13
points checked before release
Preparing letters and messages
How it works
How it is done today
A personal letter takes fifteen minutes, so in the end people send a template with the name swapped in. Nobody reads those. By hand you get twenty a day instead of two hundred.
What the system does
- Gathers facts about the recipient first and only then writes - the text rests on specifics
- Writes in your style: tone, length and structure are set once
- Before release the text passes an automatic check on thirteen points
- It also checks what a person would miss: made-up facts and promises nobody made
- What fails the check goes back for a rewrite, not to the employee
What it gives you
- The volume of templates with the quality of manual work
- A client never gets a text with a made-up fact
- You see which wording works, and you can lock it in
From practice
A video production company with an average deal of a quarter of a million roubles. The first version of the system passed less than a third of its texts - we worked out why and rewrote it completely. Now the system prepares drafts, and a person edits and sends them.
Sales and clients
550
companies with 11 verified fields each
Order in the client base
How it works
How it is done today
The same company is written three different ways, half the contacts have no phone, and some people left long ago. Mailings go nowhere, and reports do not add up.
What the system does
- Finds duplicates even when a company is written differently: abbreviated, misspelt, in another grammatical case
- Fills empty fields from official sources: company details, industry, head
- Flags records that are outdated or no longer fit
- Prepares the file in the format your system will accept
- Marks dormant clients worth coming back to
What it gives you
- Reports add up because the base stops splitting in two
- Mailings go to live contacts
- We do not know - we leave it empty, we never make things up
From practice
An order for 550 companies across three niches and regions: eleven verified fields for each, including company details, head and revenue. By hand that is, by our estimate, about a week of one employee's work. Plus a list of twenty-odd categories that must not be included - the system filtered them out on its own.
Product and marketing
36
brands in one 62-column table
Watching competitors
How it works
How it is done today
Once a quarter someone sits down and walks through competitor websites by hand. In between, the company simply does not know what changed on their side, in prices or in range.
What the system does
- Regularly walks through competitor websites, catalogues and marketplaces
- Picks up prices, range, new items and specifications
- Compares with the previous run and shows exactly what changed
- Puts everything into one file in your format, not a technical dump
What it gives you
- The picture updates itself, not once a quarter
- You see changes, not just the current state
- The data arrives in the shape your team already works with
From practice
A manufacturing company. We collect product data for 36 brands - from websites, marketplaces and PDF catalogues - and put it into one 62-column table, exactly the one their product development team described.
Product and marketing
10,000+
items per brand, the target volume
Running the product catalogue
How it works
How it is done today
Cards are filled in by hand, specifications arrive from suppliers in different formats, and the same product gets entered twice under different names.
What the system does
- Collects product data from several sources and merges it into one card
- Understands that "the same thing" is written differently and does not create duplicates
- Expands variants: one model in forty sizes becomes forty rows
- Fills in specifications by your template and leaves empty what is missing
- Picks up new items on its own, without manual entry
What it gives you
- A complete catalogue without manual input
- One format no matter who sent the data
- Fewer returns and questions caused by wrong specifications
From practice
The same project: the target volume is more than ten thousand items per brand. Everything is written straight into a working file of the right shape, not into an intermediate dump someone later sorts out by hand.
Product and marketing
268,000+
followers without a single new shoot
Publishing content across platforms
How it works
How it is done today
A content manager copies the same material to five places, keeps track of the schedule and logs it in a separate spreadsheet. Half the working day goes into copying.
What the system does
- One queue for all platforms: prepared once, published everywhere
- Pre-checks the material: what can be published and what cannot
- Schedule and statistics in one place
- Short clips are cut from the existing archive - no new shoots
- Voice-over when volume is needed
What it gives you
- One person runs as many platforms as a team used to
- The archive starts working instead of sitting there
- Posts do not slip because of holidays or weekends
From practice
A content project: 22 accounts, more than 268,000 new followers and over 10 million views in eight months - entirely from footage that already existed, without a single new shoot.
Documents and back office
almost600,000
export rows turned into a report with conclusions
Working through documents and archives
How it works
How it is done today
To answer one question you have to reread a hundred documents or half a year of correspondence. Usually nobody does it, and decisions are made by feel.
What the system does
- Reads documents, scans, correspondence and recordings and pulls out what matters: dates, amounts, parties, terms
- Puts what it found into a table you can already work with
- Under every conclusion it quotes the source document
- Builds a timeline: what happened and when
- The output is a finished document or table, not a technical dump
What it gives you
- An answer in an hour instead of a week
- Any statement can be traced back to its source
- Knowledge stops depending on who remembers what
From practice
Working through a large correspondence archive: a day-by-day timeline, tables of discrepancies, collections of quotes by topic. In another job an export of almost 600,000 rows became a report with conclusions and a visual map that a person can read, not only a specialist.
Documents and back office
500+
companies checked as one list
Checking counterparties
How it works
How it is done today
Before a deal someone opens the registries by hand and looks the company up. There is no time to check everyone, so checks are selective and usually happen after something has already gone wrong.
What the system does
- Finds the company in official sources by name, website or company details
- Builds a card: company details, head and founders, industry, revenue, age
- Flags what deserves a closer look
- Checks in bulk: not one company at a time, the whole export at once
- Keeps what was visible at the moment of the check
What it gives you
- A check takes seconds and covers everyone, not a sample
- One card instead of five open tabs
- The archive keeps proof that the check was done
From practice
A set of ready tools that go to official registries and directories on their own. Used in different jobs: from checking a list of 500-plus companies to restoring company details when only the website address is known.
Documents and back office
1
version of the numbers instead of five
Regular reports
How it works
How it is done today
At the end of the month someone pulls a table together from five sources. Two days of work, and the numbers are still disputed: every department has its own version of the truth.
What the system does
- Pulls data from your systems and spreadsheets on its own, on a schedule
- Calculates plan and actual, broken down by project, client and line of business
- Converts currencies at the rate on the transaction date
- Delivers the report in the usual form: a table, a dashboard or a file by email
- Keeps the edit history: you see who changed what
What it gives you
- The report is ready on its own and on the right date
- One version of the numbers instead of five
- Month-end closing shrinks from days to hours
From practice
We work in a system like this ourselves every day: projects, money, tasks, plan and actual, sync with working spreadsheets. Nobody had to move out of the spreadsheets they were used to - people work as before, and the data adds up automatically.
How the team works
10
minutes for a newcomer to see where things landed
Meetings → decisions and tasks
How it works
How it is done today
After an hour-long meeting nobody writes the minutes. A month later no one remembers what was agreed, and half the discussion happens all over again.
What the system does
- Turns the meeting recording into text
- Pulls out decisions, agreements, deadlines and owners
- Puts them into a short note in the same format every time
- Links it to earlier discussions of the same topic
- Lists separately what is still undecided
What it gives you
- Agreements are not lost between meetings
- A new person understands in ten minutes where things landed
- People come to the next meeting not from scratch
From practice
We do this for ourselves every working day: meeting recordings become notes with decisions and next steps, all linked to each other. That is why going through our own archive of work for this collection took hours, not weeks.
How the team works
17
lines of work in our own base
The company knowledge base
How it works
How it is done today
Knowledge lives in heads and in chats. One person goes on holiday and the process stops. A newcomer takes months to get up to speed and keeps pulling colleagues all that time.
What the system does
- Collects documents, policies, decisions and correspondence in one place
- Answers questions from these materials and shows where each answer comes from
- Suggests related things: there was already a decision on this topic, here it is
- If the answer is not in the documents, it says so instead of inventing one
What it gives you
- Answers instead of "ask Igor, he knows"
- A new employee gets to normal work faster
- Knowledge stays in the company instead of leaving with a person
From practice
Our own base: seventeen lines of work, the history of decisions, post-mortems and policies. Every working session starts with reading it rather than asking colleagues - and that is the only reason we can run so many projects at once.
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Three rules that make this trustworthy
The biggest fear with AI is that it confidently invents what is not there. Here is what we do so that it does not happen.
We do not make things up
No data - the field stays empty. Every value has a source you can open and check. This rule matters more than speed and a nicely complete table.
We check before a person sees it
The result passes an automatic check before it reaches an employee. What fails goes back for a rewrite, not into work. The check also catches what a person would miss.
A person decides
The system finds, prepares and suggests. Send, sign, call - the employee decides. We never build schemes where a robot acts on your behalf without asking.
A pilot process in one to three weeks
We price after the walkthrough: from how much time the process eats now.
- A call and a walkthrough
- Pilot process
- Rollout
- Support
What we need from you to start
You do not need to change your systems, retrain the team or buy licences.
Access to data
An export from your system, access to spreadsheets or a folder with documents. You can start with any volume, even a hundred records.
Examples of "done right"
10-20 examples of what you consider a good result, and a few bad ones. That is clearer than any technical specification.
One owner
A person who knows the process from the inside and can answer questions. A couple of hours a week from them is enough.
When we say "no" or "something else first"
We have already turned down tasks for exactly these reasons. It is a normal part of the work.
We will say it plainly
- The task is one-off: it is cheaper to do it by hand, and we will say so
- The data is such a mess that there is nothing to automate yet: first we put it in order
- The process rests on personal arrangements: AI will not help there
- The decision requires responsibility and a signature: that stays with a person
On the technical side
- Some corporate systems need separate work: we discuss it before starting
- We work with open data and with data you give us access to
- We do not use dubious sources of personal data and do not offer them to you
- Robocalls and voice calls are not what we do
Name one task that repeats every day and annoys everyone
We will look and tell you honestly whether we can take it over. The call takes 30-40 minutes, and afterwards we send a short email: what can be automated, how fast and what it will take.
Name a task