Case studies

Work with numbers before and after

Wholesale · 1C + Bitrix24

AI Sales Employee on 1C + Bitrix24

tasks from memory20 deals a day

An autonomous agent reads 1C, finds debtors, dormant customers and stock shortages — and creates tasks for sales reps in Bitrix24 by itself, each with a ready-made call brief. The very first run surfaced 18 debtors and 143 short-stocked SKUs. 1C is read-only; writes to the CRM go through an allowlist of nine operations.

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Furniture manufacturing · Ufa · client project

MebelRoom — website, calculator and request tracking

1 page on a site builder132 pages + CRM

A furniture manufacturer with revenue in the tens of millions a month was living with a one-page website. Now: a catalog of 100 real projects with filters, a calculator with a PDF quote, and every request automatically becomes a lead in Bitrix24 with its source and UTM tags. Plus a set of rules for the sales team: what to do with a request next. Launched in a month, domain migrated with zero downtime.

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Bitrix24 + Telegram · client project

AI Sales Supervisor

exports and pivot tablesa question in Telegram

The CEO talks to the CRM like a live analyst: pipeline, revenue by source, rep KPIs — the answer comes back as a finished report. The system watches unanswered leads and stalled deals on its own — 1,815 deals under control. The third system built for this client.

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Bitrix24 → Telegram · manufacturing

“Production PM” — order tracking

a customer complaintan alert the day it stalls

A system for a furniture manufacturer: it tracks order stages in Bitrix24 via REST and, when an order sits longer than the standard allows, notifies the person responsible in Telegram. Overdue orders surface the day they stall, not when an unhappy customer calls.

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Bitrix24 · data control

The “Auditor” — data discipline in Bitrix24

manual CRM checksa daily report in Telegram

A data-quality Telegram bot for a furniture company. Every day it checks deals and records — empty fields, broken statuses, stalled stages — and sends the people responsible a report. “Dead” deals have vanished from the CRM, and the manager sees how disciplined the database is without checking by hand.

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Multi-agent system

An AI Agent Fleet runs the product on its own

2–3 days of manual worka 3-line report at 08:30

Eight autonomous AI employees — an economist, a CRO, a data analyst, virality, customer support, a product strategist, a content marketer and a supervisor — track the product's metrics, run the unit economics and send the owner a short digest every morning. The whole fleet of 8 agents — 45,000 ₽/mo instead of an entire department's payroll.

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Own product

A website as proof

telling the story in wordsa verifiable showcase

Selling development work rested on chat threads and retelling — before a call, a client couldn’t verify anything. Now everything can be checked before the conversation: case studies with before → after metrics, two pricing calculators, a live dialogue with an agent above the fold. Every edit reaches the production domain in 1–5 minutes with no human involved.

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Own product

Personal AI Knowledge Base

sorting notes by hand0 minutes a day

Thoughts are written as a single stream into a notepad from a phone or a computer — no tags, folders or formatting. Twice a day an autonomous agent turns what was written into atomic notes with links and topic maps. The human confirms nothing — safety rests on technical safeguards, not on the owner’s vigilance.

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In-house product · e-commerce

A factory for personalized children's books

three specialistsone questionnaire

An in-house product — this is how I test technology with my own money before putting it into your business. The child becomes the hero of the book, and their appearance stays consistent on every page. Text, illustrations and the print layout are assembled from a single Telegram questionnaire — no author, illustrator or layout designer. Files pass the print shop's validation automatically, and the print run arrives by courier.

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