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Fake engagement check for @n2d2ai

N2D2 AI - нейросети для контента — public reach metrics and manipulation-risk assessment dated 2026-08-15.

Заказать ИИ-агента: n202.ru Для связи: @elena_novokhatskaia Новости об ИИ-агентах, нейросетях и вайбкодинге для бизнеса. Промпты и практический опыт. Автоматизации n8n, LangChain и OpenClaw.

91/100
cleanliness index
Grade A+
low manipulation risk
Subscribers
25355
Median views
16468
ERR
64.9%
Posts sampled
40
Niche
Technology

Evidence snapshot

The @n2d2ai assessment dated 2026-08-15 uses 40 recent public posts. At that snapshot the channel had 25,355 subscribers, median post views were 16,468, ERR was 64.9%, and the cleanliness index was 91/100.

Source: public Telegram counters captured during the saved check. The result can change after a new snapshot.

Advertising outlook

Advertising placement: reasonable.

Estimated 48-hour reach: 10,385–13,963 views.

What grade A+ means

The channel shows almost no signs of manipulated engagement. Its public reach and audience activity are consistent with the subscriber count.

Run a fresh check for @n2d2ai

This page shows the saved result dated 2026-08-15. The bot collects a new snapshot for a current report.

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Monitoring reruns the assessment and sends an alert when ERR drops, subscribers change abnormally, or the cleanliness index moves.

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Questions about @n2d2ai

What does grade A+ mean for @n2d2ai?

The channel shows almost no signs of manipulated engagement. Its public reach and audience activity are consistent with the subscriber count.

What is the ERR of @n2d2ai?

ERR is 64.9%. Median post views equal 64.9% of the channel's 25,355 subscribers. ERR describes observed reach, not proof that every remaining subscriber is fake.

How does TG Inspector calculate the cleanliness index?

The 91/100 index combines several public-data signals, including reach relative to audience size, audience behavior, and channel metadata. It is a probabilistic assessment, not proof of intentional manipulation.

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This automated assessment is probabilistic. It describes statistical signals in public data and does not claim intentional manipulation. Channel owners can run a new check or contact support to request removal.

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