Case study

Inboxy AI

AI & Productivity · Own product — Telegram bot + iOS app

Inboxy AI, our own product: an AI knowledge inbox that turns shared links, videos, PDFs and voice notes into summaries, tags and a daily digest — a Telegram bot and a native iOS app on one knowledge base.

Own productAITelegram botiOS app2026

Inboxy AI. Save anything. Remember everything.

  • Telegram bot
  • iOS app
  • Android and web — next
The Inboxy AI inbox on a phone — saved items with tags and search
What it is

An AI inbox for everything you meant to come back to

Share a link, a video, a PDF or a voice note and Inboxy extracts the key points, tags and files it, and finds it again by meaning — in a Telegram bot and a native iOS app, built on one shared knowledge base.

12kinds of content it reads
7services around one database
3languages from day one — EN, UK, RU
How it works

From a shared link to a briefing

Four stages, each with a fallback, so a TikTok without captions gets the same treatment as a well-formed article.

  1. Save

    Share from any app on the phone, or drop a link, a forwarded post, a PDF or a voice note into the Telegram chat.

  2. Extract

    A cascade of extractors: native subtitles, yt-dlp plus Whisper, a headless browser, and Gemini Vision reading text off video frames when nothing else works.

  3. Understand

    A one-line gist, key points and actions; a title, category and tags; a quality score; a 3,072-dimension embedding for search by meaning.

  4. Return

    Semantic and hybrid search, /ask answers with their sources, duplicate and related-item detection, and a daily digest.

Sources it understands

  • YouTube
  • Instagram
  • TikTok
  • Threads
  • Facebook
  • Telegram posts
  • GitHub
  • Reddit
  • Notion
  • Any web page
  • Voice notes
  • PDF and text
Telegram bot

Telegram first: zero-friction saving

The bot is where the product started. Forward a post, paste a link or send a voice message; the status message updates live while the worker extracts and summarises, then the summary comes back with actions — ask, related, fact-check, share.

The Inboxy Telegram bot returning a summary with key points, tags and a category for a saved link
A saved link, summarised
The Inboxy Telegram bot showing the actions under a saved item — ask, related, fact-check, share
Actions on every item
iOS app

A native app for the rest of your phone

A Flutter app with a share extension, so anything on the phone can be saved without opening the chat: inbox with inline search and favourites, item pages with per-item questions, fact-check and translate, voice notes and screenshot capture, and stats.

Inboxy iOS app — the inbox with saved items, tags and search
Inbox
Inboxy iOS app — an item with its summary, key points and actions
Item detail
Inboxy iOS app — asking a question across everything saved
Ask
Inboxy iOS app — statistics of saves by category and source
Stats
Design

Designed in Pen, screen by screen

Dark and light themes, an editorial component set, and the brand type — Bricolage, Inter and Space Mono — carried from the design file into the app.

Design — the onboarding screen
Onboarding
Design — the inbox, dark theme
Inbox
Design — an item with summary and key points
Item detail
Design — the ask screen with an answer and its sources
Ask
Design — adding a link, a note or a voice recording
Capture
Design — statistics of saves
Stats
Design — settings with language, digest time and export
Settings
Design — the inbox, light theme
Light theme
Under the hood

Seven services, one Postgres

It began as a single bot and grew into an ecosystem: the bot core, an extractor on the host, the mobile app, an admin dashboard and three social monitors for YouTube, Instagram and Threads — all around the same database.

  • Bot and queue

    grammY on Node and TypeScript; BullMQ on Redis so the bot answers instantly and the heavy work runs in a worker with a live status message.

  • One database

    PostgreSQL with pgvector — vector search inside the database, Drizzle for typed queries and additive migrations.

  • AI

    Google Gemini for summaries and categorisation, gemini-embedding-001 for embeddings; Groq Whisper and a local Whisper for speech.

  • Extractor service

    Runs on the host, not in Docker: it needs Chrome DevTools, yt-dlp, ffmpeg and local Whisper. The bot reaches it over the Docker host bridge.

  • Mobile app

    Flutter with a native share extension; sign-in with Apple, Google, an email code, or one tap from Telegram through a deep link and a match code; voice notes and screenshot capture.

  • Delivery

    Multi-stage Docker builds; a merge into main deploys to production and applies the migrations — no manual steps.

Principles

What the product refuses to do

The engineering that mattered most was not capturing content — it was earning trust and bringing people back.

  • Trust, then verify

    Placeholder or too-short content never reaches the model — the bot returns an honest stub instead. Prompts forbid guessing; every summary carries a quality score.

  • A briefing, not a backlog

    People save eagerly and rarely come back. The daily digest, reviews, reminders and related-item links exist to bring the value back to them.

  • Search the way you think

    Hybrid retrieval — text match plus vector similarity — ranked by relevance, freshness, the user’s own ratings and extraction quality.

  • No lock-in

    The whole knowledge base exports to Markdown and JSON at any time. Free covers 50 saves a month; a Pro plan for heavy savers is on the way.

Six months from the first commit

  1. Mar 2026First commit. The pipeline moves to the Gemini API on day one.
  2. Apr 2026The busiest month: the Instagram and YouTube monitors, the admin dashboard, automatic migrations on deploy, and the rename from iSaved to Inboxy AI.
  3. May 2026The Flutter app: voice notes and screenshot capture, fact-check and translate, native share, tappable answer sources.
  4. Jun 2026Free and Pro limits, export without lock-in, spaced-repetition review, a single to-do list.
  5. Sep 2026inboxyai.app, the API behind HTTPS, sign-in with Apple and Google, and the iOS app on its way to the App Store.
Inboxy AI app icon

Inboxy AI × Jellyworkz

Our own product: the bot, the pipeline, the app and the design, built and run by Jellyworkz. Free at inboxyai.app and t.me/InboxyAIBot.

Product
Jellyworkz
Work
Product, design, Telegram bot, iOS app, backend
Stack
TypeScript, Flutter, PostgreSQL + pgvector, Gemini
Since
March 2026

The idea

Everyone saves links and nobody comes back to them. Inboxy AI is Jellyworkz’s own answer: share anything to a Telegram bot or the iOS app, get the key points, a category and tags back within seconds, and find it again later by meaning rather than by keyword — with a daily digest that brings the value back instead of leaving a backlog.

What we built

A Telegram bot on grammY with a BullMQ worker and live status updates; an extractor service running a cascade of strategies — native subtitles, yt-dlp with Whisper, a headless browser, Gemini Vision on video frames — for YouTube, Instagram, TikTok, Threads, Facebook, Telegram, GitHub, Reddit, Notion and any web page; summarisation, categorisation, quality scoring and 3,072-dimension embeddings on Gemini; hybrid search and /ask answers with sources over PostgreSQL and pgvector; a Flutter iOS app with a share extension, voice notes and one-tap sign-in; an admin dashboard and three growth monitors — seven services around one database, deployed automatically on every merge.

Where it stands

Six months from the first commit to a product with Free and Pro plans, export without lock-in, and three languages. The Telegram bot is live at t.me/InboxyAIBot, the iOS app is built and heading to the App Store, and Android and web clients are next.