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The NEAT Project {RE-TOWER}

The NEAT Project {RE-TOWER}

A Roblox experience owned by The NEAT Project {RT}.

ObbyENTower of HellObbyCommunity Content

Description (written by the developer; not a statement by this register)

This game is heavily inspired by The NEAT Project and is a more community-based version. If you want to submit a tower, please join our server! This entire game was made by just two people (plus community towers), so expect bugs and please report them. Tags: Tower of Hell, Tower, TNP, NEAT, Tower, ETOH, JTOH, Towers, The NEAT Project

Last updated by the developer 24 Jan 2026, 15:34 UTC.

0
playing (measured 24 Aug 2026, 07:21 UTC)
1,574
lifetime visits
77%
liked (10 👍 / 3 👎)
15
favourites (9.5 per 1k visits)
2 June 2025
created (per Roblox)

Play on Roblox →

Live players over time

Growth

Growth history is still building. We hold one measurement for this entry. A trend needs at least two, taken days apart — so this will fill in on its own rather than being estimated. We do not publish numbers we have not measured.

Measurement log — every players count we have recorded
Measured (UTC)PlayersChange
24 Aug 2026, 07:210first reading

Concurrent players at each of our measurements (insert-on-change).

Badge funnel

Enter the Lonely Valley! · progression742 · 100.0% win
NEaLoTV · progression346 · 100.0% win
NEaSD · progression243 · 100.0% win
NEaBananaSandwich · progression185 · 100.0% win
NEaSH · progression140 · 100.0% win
NEaMildSauce · progression107 · 0.00% win
NEaFD · progression97 · 0.00% win
NEaHC · progression95 · 0.00% win
NEaReddyRed · progression90 · 0.00% win
NEaBH · progression50 · 0.00% win
NEaCC · progression46 · 0.00% win
NEaLV · progression41 · 0.00% win
NEaLC · progression24 · 0.00% win
NEaCM · progression9 · 0.00% win
NEaL&L · progression6 · 0.00% win

How many players have ever earned each badge — a proxy for how far players get before they stop. Steep drop-offs mark where a game loses people. Win rate is the past-day share of players who earned it; categories are assigned by a language model from each badge’s own name and description.