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Channel

Lenta Tech

@LeTeam_LentaTech

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

653subscribers

-3 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1002554660700
TypeChannel
Username@LeTeam_LentaTech
CreatedBetween 1 March 2025 and 31 July 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded8 August 2026
Last confirmed live16 August 2026
Measurements held3
Confirmed unchanged1 time, most recently 16 August 2026
On Telegramt.me/LeTeam_LentaTech

Growth

653656654.57 August 2026 — 656 subscribers8 August 2026 — 656 subscribers16 August 2026 — 653 subscribers7 August 202616 August 2026
3 measurements spanning 9 days, net -3. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 653–656 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
16 Aug 2026, 07:27653-3
8 Aug 2026, 02:45656no change
7 Aug 2026, 18:14656first reading

Engagement

10 posts held, back to 23 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
39.9%
avg views ÷ 653 subscribers
Avg views / post
260
9 posts measured
Reaction rate
4.23%
reactions ÷ views · ER floor
Posts in window
10
of 10 held

ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.

ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.

What these figures were computed from
WindowRolling 30 days · latest post in window 6 August 2026
Posts held10 (23 July 20266 August 2026)
Views total2,342
Reactions total99
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken8 Aug 2026, 02:45 UTC

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

What this channel posts

Video runtime
15s
Average length
8s

Measured directly from 2 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no mark.

Reaction mix

99 reactions across 9 posts, in 11 distinct kinds. The most used accounts for 28.3% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥2828.3%
custom 54293566695596729722121.2%
1313.1%
🥰1212.1%
👏88.08%
👍77.07%
custom 542910455068443065033.03%
😁22.02%
🤝22.02%
🦄22.02%
😎11.01%

Custom emoji. 2 of the rows above are Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The counts beside them areTelegram’s.

No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.

Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.

Coverage. Reactions were read on 9 of the 10 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 99reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 10 most recent posts we hold, published 23 July 2026 to 6 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.

Recent posts

6 Aug 2026, 09:05 UTC150 views14 reactionsread 8 August 2026
Photo

Теперь сообщить, что вы не на связи, можно одной аватаркой ☺️ Собрали набор на разные случаи: отпуск, больничный, командировка, day off и мероприятие. Выбирайте подходящую, ставьте на время — и коллеги сразу поймут, куда вы пропали 🤓 ➿➿➿➿ Заглядывайте в другие наши соцсети: 👤 ВК 📢 Макс

custom 54293566695596729728🔥6

4 Aug 2026, 07:02 UTC178 views8 reactionsread 8 August 2026
Photo

💛 Стартовал ежегодный опрос ЭКОПСИ об IT-брендах работодателей. Если вы уже знакомы с нами, будем рады узнать ваше мнение. Оно поможет лучше понять, как сегодня воспринимают Lenta tech. 👉 Пройти опрос Что важно знать: ✔️опрос полностью анонимный, все ответы будут представлены только в обобщенном виде; ✔️пройти его можно с любого устройства до 31 августа; ✔️кроме Internet Explorer — в этом браузере возможны ошиб

6custom 54293566695596729722

1 Aug 2026, 08:24 UTC241 views10 reactionsread 8 August 2026
Photo

В центре внимания — адресное хранение 😎 На Российском Ритейл Шоу в апреле этот доклад вызвал ажиотаж и огромное количество вопросов. С презентацией решения тогда выступала Алла Антонова, директор ИТ торговой сети «Гипер Лента», и сегодня мы возвращаемся к нему, чтобы разобрать всё по полочкам. В карточках рассказываем, как устроена архитектура, какие четыре типа задач помогают системе понимать, что полка пуста. И к

7👍2custom 54293566695596729721

30 Jul 2026, 11:02 UTC269 views9 reactionsread 8 August 2026
Photo

Lenta tech выходит за пределы ретейла! 🚀 Совместно с шинным холдингом «Кордиант» мы в тестовом режиме внедрили технологию компьютерного зрения на Ярославском шинном заводе. Решение автоматически распознает более 30 типоразмеров шин, подсчитывает и классифицирует продукцию на всех этапах производства — от сборки до вулканизации — с точностью более 95%. Это помогает контролировать запасы в режиме реального времени, б

🔥4👍3🤝2

29 Jul 2026, 11:02 UTC229 views11 reactionsread 8 August 2026
Photo

Ручная выдача доступов кажется рабочим решением... ровно до тех пор, пока пользователей не становится десятки тысяч. Дальше начинаются очереди, ошибки, лишние права и бесконечная рутина 🫣 Андрей Софронов, тимлид продукта управления доступами Lenta tech, в своей статье делится опытом внедрения IDM и рассказывает: • почему автоматизация стала необходимостью; • с какими вызовами столкнулась команда; • как пришлось п

🔥10😎1

28 Jul 2026, 08:34 UTC261 views8 reactionsread 8 August 2026
Video

В «Ленте» спрос на миллионы товарных позиций давно не считают в таблицах, а предсказывают с помощью машинного обучения. Главная цель — найти золотую середину: чтобы и товар не залеживался (списания), и полки не пустели (упущенная выручка). Впечатляющие факты: ✔️Система пересчитывает ежедневно 15 млн временных рядов для 2500 магазинов и 50 товарных групп. На основе этих данных формируют реальные заказы для поставщик

🔥5👏3

26 Jul 2026, 08:15 UTC335 views19 reactionsread 8 August 2026
Video

✨Магия нашего офиса ✨ ➿➿➿➿ Заглядывайте в другие наши соцсети: 👤 ВК 📢 Макс

🥰12👏4😁2👍1

24 Jul 2026, 15:16 UTC382 views10 reactionsread 8 August 2026
Photo

Ловите крутую пятничную новость — в августе мы проводим Lenta Tech Meetup ⚡️ AI-агенты в деле: когда нейронка перестаёт отвечать и начинает работать Нейронки уже давно умеют отвечать на вопросы, генерировать тексты и помогать с рутиной. Но что происходит, когда ИИ становится не просто собеседником, а полноценной частью рабочего процесса? 📍20 августа в 18:30 / Онлайн В программе — три взгляда на то, как ИИ переста

custom 54293566695596729726🔥2👏1🦄1

23 Jul 2026, 09:03 UTC297 views10 reactionsread 8 August 2026
Photo

Распознать ценник на фото? Звучит не так уж сложно. А если он смазан, снят под углом, частично закрыт товаром, да еще и робот все это снимает на ходу? Тут задача уже со звездочкой. Или даже с двумя 🤖 Команда Lenta tech превратила эту инженерную головоломку в ML-хакатон и предложила участникам найти решение, которое можно использовать в реальном ретейле. В новой статье на Хабре рассказываем: — почему детекция ценни

custom 54293566695596729724custom 54291045506844306503👍1🔥1🦄1

Showing the 10 most recent of 10 posts we hold for @LeTeam_LentaTech. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.

Citation-graph rank

Citation-graph rank — 1,065,368 of 1,548,671entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

Mentions

Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.

Named by

Channels on the register whose posts name this channel's handle.

A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.

Cite this entry

A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 16 August 2026 — this entry's latest reading, not the date you are reading this.

“Lenta Tech” (@LeTeam_LentaTech), 653 subscribers as measured 16 August 2026. Telegram Register, tgregister.com/channel/LeTeam_LentaTech.

Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.