Use cases

AI for business reports and spreadsheets

The agent pulls a report together from 1C, CRM and marketplaces, works out revenue, margin and conversion, and hands you the table before the meeting.

Scenarios for this job

Every scenario is a ready brief for the agent: the steps, the connected systems and the output. Open one and run it on your own data.

Get a recurring cash-flow report on schedule

Your morning starts with the bank client and three tabs of balances. The agent posts yesterday's summary to Telegram and flags what stands out.

FinanceAutomation
A revenue-by-channel dashboard refreshed on schedule

Every Monday someone rebuilds the same report by hand, and it still misses the meeting. Here it rebuilds itself in Google Sheets, on time.

AnalyticsAutomation
Merge sales from 1C, CRM and marketplaces into one table

The same item is called three different things in 1C, the CRM and the marketplace. Sales land in one table, with the leftovers listed openly.

AnalyticsAnalysis
Find margin anomalies over the last weeks

Revenue holds steady, yet less money is left at the end. Margin — what a sale leaves after costs — gets counted per item, week by week.

AnalyticsAnalysis
Compare this month with last by revenue and orders

The owner asks one question: better or worse, and by how much. Both months are counted by a single rule, with the caveats spelled out.

AnalyticsAnalysis
A weekly all-channel report with ROMI and conclusions

On Monday you have to say which channel brought money, not just which one spent it. The agent pulls spend and revenue per channel for the week.

MarketingAnalysis
A leads and cost-per-lead (CPL) dashboard for the stand-up

The ad account shows more leads than the CRM and nobody explains the gap. The agent links spend to deals in Bitrix24 and works out cost per lead.

MarketingAnalysis
Build a weighted pipeline forecast

The quarterly review costs two days in Excel before the meeting. The agent pulls plan against actual, who contributed what, and the open-deal forecast.

SalesAnalysis
A weekly sales summary for the head of sales

Someone assembles the Monday numbers on Sunday night. The agent posts the week to Telegram on its own — on time, and short enough to read.

SalesAutomation
Build a cash flow statement for the period

The report shows profit, the accounts show nothing. The agent lays out how much the business itself earned and how much went into kit and loans.

FinanceAnalysis
Measure receivables turnover by counterparty

You changed the payment terms, but nobody checked whether customers actually pay faster. The agent shows average payment days by month and by client.

FinanceAnalysis
Build a dashboard in Excel or Google Sheets

The file falls apart after every fresh export: ranges shift, slicers come loose. This one is built to survive the next paste-in and the one after.

AnalyticsAnalysis

A report is not a button, it is an assembly job. Revenue sits in 1C, deals sit in Bitrix24 or amoCRM, sales and platform deductions sit in the Wildberries and Ozon back offices, ad spend sits in Yandex Direct, cash sits in the bank statement. To produce one line — how much did we make last week — you pull four or five systems, align them to the same periods and the same product catalogue, then explain why the number disagrees with accounting. By next Monday the whole thing starts over. This cluster holds nine scenarios, from a morning cash digest to a quarterly pipeline picture and a leads-and-CPL dashboard.

Today a person does that in Excel: one export per source, one tab per export, lookups on SKU codes, manual repair of the rows where product names drifted apart. An hour or two a week for a recurring digest is the optimistic estimate; a monthly channel report eats a working day. The time is not the expensive part. The expensive part is that the report lands after the decision was made, and everyone who edited it keeps a copy, so the meeting opens with an argument about whose version is current. Then come the follow-up questions, answered by hand out of the raw exports.

The agent runs the same assembly on a schedule. It reads 1C over OData, Bitrix24 and amoCRM, MoySklad, the Wildberries and Ozon back offices, Yandex Direct and Metrica and your bank statement, aligns everything by period and product, computes revenue, margin, ad share, CPL and conversion, then writes the result into Google Sheets or sends a short digest to Telegram. You describe the rules once, in plain words. One-off questions work the same way: ask it to compare margin by category against last quarter and it builds a slice no template ever had. The boundary is firm — the agent reads what already exists in your systems, changes nothing in them and does not replace management accounting. Discrepancies get shown and explained, not smoothed over; which number is right stays your call.

Common questions

Where does the agent get the data for a report?

From whatever you connect: 1C over OData, Bitrix24 and amoCRM, MoySklad, the Wildberries and Ozon back offices, Yandex Direct and Metrica, bank statements and Google Sheets. It reads them through their APIs, so nobody exports files by hand.

How is an AI agent different from a BI dashboard?

A dashboard shows the slices someone modelled in advance. You ask the agent in plain words and it assembles a cut that was never in the dashboard, right in the chat. Anything you need regularly then goes on a schedule and arrives on its own.

Does the report refresh itself?

Yes. Any scenario can run on a schedule — every morning, every Monday, or on the first day of the month. The agent rebuilds the report on fresh data, appends a sheet in Google Sheets and drops a short summary into Telegram. Nothing to launch by hand.

What if 1C and the marketplace back office disagree?

The agent shows the gap and names the cause: different revenue recognition periods, orders never bought out, platform commissions and deductions. It never bends one number to match the other — it puts both side by side and lets a person decide.