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An engineer's notes on bringing AI into business

Guides for owners and managers: what implementation costs, where off-the-shelf solutions break, what the law allows you to send to an AI model. I write about what I've tested on my own projects, with figures, timelines and caveats.

All posts · 6
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  1. 13–15 min read

    What AI implementation costs: rates and six estimates

    My rates and six cost estimates with payback periods: a ₽600K shop process audit, ₽480K for 1C access via Telegram, an AI security check from ₽45K.

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  2. 12–15 min read

    AI receptionist and booking chatbot: where it breaks

    What an AI receptionist and booking chatbot is made of, the four places it breaks in real use, and nine questions to ask a vendor before you pay.

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  3. 11–14 min read

    Inventory sync between 1C, Wildberries and Ozon

    Why stock in 1C and on the marketplaces doesn't match: different SKU codes, units of measure and stock registers. How to line it up step by step, and when you don't need a sync.

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  4. 11–13 min read

    Telegram bot for 1C: access without the 1C client

    How to give field staff access to 1C data via Telegram without exposing 1C to the internet: built-in HTTP services, an encrypted tunnel, per-site permissions.

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  5. 11–13 min read

    Personal data and LLMs: 152-FZ and ChatGPT

    Can you send customer data to ChatGPT? What 152-FZ requires, why anonymisation often fails, and how to check your own system in 20 minutes.

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  6. 14–17 min read

    How I went from factory ERP systems to my own AI services

    Nine years as an engineer: a shipyard, ERP systems for European factories, ad buying and my own AI services. What each stage taught me and what it means for you.

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