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RU

An AI spoken-English coach inside Telegram that people actually open every day

Big Ben helps adults beat the fear of speaking: voice, instant corrections, memory and emotionally engaging characters turn practice into daily conversations worth continuing.

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Zara — Big Ben character
Zara
Big Ben · voice & text
Why did you choose this neighborhood?
Because it is more cheap than center.
BetterBecause it’s cheaper than the center.
NaturalIt’s way more affordable than downtown.
  • $91.6B 1

    Online language-learning market by 2030

  • 1B 5

    Telegram MAU — launch with no separate app

  • ~1.5B 7

    people learning or using English

  • ~93 min 6

    avg AI-companion session length

Big Ben helps adults practise English in Telegram with AI characters — combining voice role-play, instant corrections, natural phrasing and retention driven by emotional engagement.

Why now

  • LLMs and voice AI made personal speaking practice cheap and scalable.
  • People want to speak, not just tap through exercises.
  • Telegram lets us ship a real product with no separate mobile app.
  • AI tutors are becoming a commodity — retention, not just answer quality, wins.
  • Emotionally engaging characters build the habit of coming back.
1B 5

Telegram MAU (Mar 2025) — launch with no separate app

52.7M 4

Duolingo DAU, 12.2M paying (Q4 2025), DAU +30% YoY — the category scales and monetizes

~93 min 6

avg AI-companion session (Character.AI) — emotional engagement retains

~1.5B 7

people worldwide learn or use English

Thesis

AI tutors are becoming a commodity. The winner isn’t the model’s answer — it’s the habit of coming back.

We build a relationship, not a lesson: characters worth speaking English with every day. That is our retention engine.

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Product already in MVP

See the product, not just the idea

A typical session: pick a character → voice/text → a live correction → progress.

  • Telegram onboarding
  • Character selection
  • First voice/text turn
  • Correction flow
  • Progress and reports
  • Admin console for characters and scenes
С кем поговорим сегодня?
ZaraZara
LinaLina
KaiKai
LeoLeo
MayaMaya
EmmaEmma
Zara
Zara
онлайн
Tell me about your day — keep it casual.
0:05
Today I working from a cafe.
Love that. Tiny fix so it sounds native:
BetterToday I’m working from a cafe.
NaturalI’m working from a cafe today — nice change of scenery.
Tip«I’m working» — Present Continuous для того, что прямо сейчас.
I’m working from a cafe today.
5дней подряд
+18natural phrases
32мин практики

Вернёшься завтра — серия продолжится.

Выбираешь, с кем говорить
Open the live demo in Telegram

Learners quit — not because of content

They quit because practice is boring, stressful or irregular.

  • Human tutors are expensive and tied to a schedule.
  • Language apps scale but rarely engage emotionally.
  • Generic AI tutors are useful but faceless.
  • Companion apps hold attention but don’t teach structured English.
  • Fear of speaking blocks progress more than grammar does.

Big Ben turns English practice into a relationship-like learning loop — safe, structured and measurable.

10+ AI charactersTelegram-first experienceVoice and textGuided scenesFree conversationInstant correctionsNatural English alternativesHints in your languageVocabularyProgress and session reportsSafe flirt boundariesAdmin console for content at scale

Large market, narrow entry

The global language-learning market is huge and growing. We enter through a fast-growing segment — AI English practice — and a focused niche: Russian-speaking adults in Telegram.

Market size: TAM, SAM, SOM TAM · $91.6B SAM · $70.7B SOM ≈$24M/yr
  • TAM · Online language learning $91.6B 1

    Global online market by 2030 (CAGR ~18%).

  • SAM · AI English practice $70.7B 23

    English as a segment by 2030 (~16% CAGR); AI-in-education grows ~31%/yr. Source-based estimate.

  • SOM · RU-speaking in Telegram ≈$24M/yr

    Serviceable market — illustrative bottom-up model (below).

SOM · bottom-up model

  • Reachable audience: RU-speaking adults, learning English, active on Telegram ≈20M
  • Target paying share at scale ≈2%
  • ARPU (≈ $5 / mo) ≈$60 / yr
= serviceable market ≈ $24M / year

Illustrative bottom-up model. Inputs are refined as we validate the funnel — not a promise, just a way to show the logic.

Market growth to 2030

Online language learning 1
2024 · $33.3 B
2030 · $91.6 B
CAGR 18.4%
AI in education 3
2024 · $5.9 B
2030 · $32.3 B
CAGR 31.2%

We start with a narrow entry: Russian-speaking, Telegram-native adults who need everyday social, travel, dating, relocation and work English — and the motivation to speak daily. Market figures are sourced; SOM is an illustrative bottom-up model.

Moat

Why this is hard to copy

The advantage compounds over time and is tied to data, content and distribution.

Retention data flywheel

Every session shows which characters and scenes retain and convert — we tune the experience, not just the model.

Character & scene library

An admin console and production pipeline let us scale characters, voices and guided scenes fast — a content moat.

Telegram-native distribution

No separate app: lower friction, cheaper starts, in-messenger virality across 1B MAU.

Trust & safety

A safe format, flirt boundaries and 18+ — something mass companion apps can’t afford inside learning.

Competition

Competitors optimise either learning value or emotional engagement. Big Ben combines both: education-first English practice with emotionally engaging characters inside Telegram.

Конкурентная карта Duolingo Duolingo Speak Speak ELSA ELSA Praktika Praktika Loora Loora Character.AI / Replika Character.AI / Replika Big Ben Big Ben Learning value → Emotional retention →
Duolingo Mass gamified learning
Speak AI speaking practice
ELSA Pronunciation focus
Praktika AI tutors
Loora AI English coach
Character.AI / Replika Adjacent emotional engagement

Business model

  • B2C subscription
  • Free → paid conversion
  • Voice-minute limits
  • Premium characters
  • Scenario packs
  • Annual plans
  • Later: B2B / B2B2C pilots

Paid packs

Dating EnglishTravel EnglishRelocation EnglishBusiness Small TalkInterview EnglishVoice Confidence Pack
Target model (assumptions), not current results.
LTV : CAC ≥ 3 : 1
Free → Paid 3–6%
Gross margin after AI/voice 60–70%

Funnel and metrics

Current stage: MVP / pre-seed validation.

Targets — not current results
Click to Telegram 100%
Bot start 75%
Onboarding done 55%
First turn 45%
First voice turn 30%
Paying 6%

Target funnel (targets), not current results. Pre-seed: we instrument and validate each step.

Metrics we track

  • Landing visitor → click to Telegram
  • Telegram start → completed onboarding
  • Completed onboarding → first turn
  • First turn → first voice turn
  • Retention D1 / D7 / D30
  • Average turns per active user
  • Voice minutes per paying user
  • Free → paid conversion
  • Paying churn
  • CAC / LTV
  • Gross margin after AI/voice costs
  • Highest-converting and highest-retaining characters

We are instrumenting the whole funnel now; cohort metrics and unit economics open to investors after NDA.

Go-to-market

Telegram channelsTikTok / Reels / ShortsEnglish-learning creatorsTravel and relocation bloggersDating and social English contentReferral mechanicsSEO pagesTeacher affiliate programRelocation/travel community partnerships

Short character-led content drives Telegram starts cheaper than classic edtech ads.

Roadmap

0–1 month

  • Public landing
  • Investor page
  • 10+ characters
  • Attribution
  • First cohort analytics
  • Demo video

1–3 months

  • Payments / paywall
  • Referrals
  • Scenario packs
  • Retention updates
  • Cohort dashboard
  • Creator campaigns

3–6 months

  • Stronger voice experience
  • Advanced pronunciation feedback
  • More characters
  • Paid-growth tests
  • B2B pilots

6–12 months

  • 30+ characters
  • Localization
  • Creator-marketplace hypothesis
  • Mobile app — only if the Telegram funnel proves the economics

Fundraising

Request the investor deck

Round: Pre-seed / Seed

Amount: on request — in the deck and on a call

Use of funds

Use of funds Product and engineering: 35% AI / voice infrastructure: 20% Growth and marketing: 20% Content and characters: 15% Safety, analytics, operations: 10%
  • Product and engineering 35%
  • AI / voice infrastructure 20%
  • Growth and marketing 20%
  • Content and characters 15%
  • Safety, analytics, operations 10%

Next milestones (~18 mo)

  • Payments and paywall, referral mechanics
  • Retention updates and cohort dashboard
  • Creator campaigns and paid-growth tests
  • B2B pilots; 30+ characters and localization

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