How to vibe codeBluedot
Invisible, privacy-first AI note taker
bluedothq.com ↗AI Meeting Assistant
The verdict: can you vibe code Bluedot?
Build a personal web-based audio upload and transcription dashboard, but skip writing native cross-platform desktop shells and browser extensions.
Replicating Bluedot's core value for personal use means dropping the native desktop wrappers and bot-free browser extension capture in favor of an audio upload tool that transcribes via Whisper and summarizes via LLMs. Building a robust system-audio capture extension that works across Zoom, Google Meet, and Teams without breaking on browser updates is a massive engineering trap for a solo developer. If you just want automated meeting summaries for personal notes, use existing tools; build this only to learn audio processing pipelines and RAG chat.
Estimated effort: 3-4 weeks of focused coding
What you can't replicate
- Zero-bot extension capture across 50,000+ corporate environments without breaking permissions
- Audited SOC 2 Type II compliance and enterprise data governance frameworks
Founded
2021
Raised
~$600,000 USD
Team
7 employees
Cheapest paid tier
$0
What Bluedot does
Bluedot captures, transcribes, and summarises meetings across online platforms and in-person without injecting virtual meeting bots.
Core features
- Bot-free audio and video recording via Chrome extension or desktop capture
- Multi-language speech-to-text transcription (100+ languages)
- Automated summaries, action items, and key highlights extraction
- Cross-meeting RAG and conversational AI chat interface
- Webhook and Model Context Protocol (MCP) data syncing
- Secure local storage and enterprise data privacy controls
The business
Pricing
- Free$0
- Basic$14/mo
- Pro$20/mo
- Business$32/mo
Funding
~$600,000 USD from Google for Startups, Daniel Gross, Greg Jakacki, Tomas James, Bridget Harris
Pay vs build, cumulative
Break-even at month 5 — after that, every month is money kept.
The hard parts of vibe coding Bluedot
- Capturing system audio and browser tab streams cleanly without virtual bot attendance or audio feedback loops
- Managing multi-platform state sync across extension, desktop shell, and web dashboard
- Building a reliable cross-meeting vector search and RAG architecture over large transcripts
- Maintaining low-latency transcription pipelines and structured LLM extraction without data leakage
How to vibecode Bluedot
Prerequisites
Node.jsfree
Required for running the Next.js full-stack framework and package manager.
GitHubfree
Source control and deployment pipeline integration.
OpenAI API AccountPay-as-you-go (~$0.006/min)
Provides the Whisper speech-to-text model and GPT-4o for meeting summaries.
AI coding tools
Recommended stack
| Frontend | Next.js with Tailwind CSS and shadcn/ui |
|---|---|
| Backend | Next.js Server Actions and API Routes |
| Database | Turso (SQLite at the edge with vector support via libSQL) |
| Auth | better-auth |
| Payments | None (Personal use clone) |
| Other | OpenAI API (Whisper STT & GPT-4o), Cloudflare R2 (Audio/Video storage) |
Hosting & infrastructure
| Vercel | Hosting the Next.js frontend and serverless API endpoints | $0-20/mo |
| Cloudflare | Storing recorded audio and video files securely in R2 object storage | $0/mo (Free tier) |
Build guide
01Project Scaffolding and Database Schema
Initialize a Next.js project with TypeScript, Tailwind CSS, shadcn/ui, and better-auth connected to Turso database.
Create a new Next.js project using App Router, TypeScript, and Tailwind CSS. Configure better-auth with email/password authentication backed by a Turso SQLite database using libSQL. Set up the initial database schema with tables for users, meetings (id, title, audio_url, transcript, summary, action_items, created_at), and chat_messages. Ensure all environment variables are properly structured in .env.example.02Audio Upload and Storage Pipeline
Implement file upload functionality for audio and video files, storing binaries in Cloudflare R2 object storage.
Build a secure audio/video upload component and corresponding API route in Next.js that accepts MP3, M4A, and MP4 files up to 500MB. Integrate Cloudflare R2 object storage (via AWS S3 client) to store the raw media files securely and return a signed playback URL. Save the file metadata and storage path linked to the authenticated user's account in the Turso meetings table.03Speech-to-Text Transcription Integration
Integrate OpenAI Whisper API to transcribe uploaded meeting audio files into structured text with timestamps.
Write a background processing service using OpenAI's Whisper API (`audio.transcriptions.create`) that downloads the audio file from Cloudflare R2, sends it for transcription with timestamp support, and saves the resulting JSON transcript text into the meeting record in Turso. Handle long audio chunking if file size exceeds API limits.04AI Summarization and Action Items Engine
Create an LLM processing step that analyzes transcripts to generate executive summaries, key decisions, and action items.
Implement an LLM summarization pipeline using OpenAI or Anthropic API. When a transcription completes, send the transcript text to the model with a structured prompt instructing it to extract an executive summary, bulleted key points, categorized action items with assignees, and a Q&A section. Store these structured outputs in JSON columns in the Turso database and display them on the meeting details view.05Cross-Meeting RAG and AI Chat Interface
Build a conversational chat interface allowing users to query insights across all past transcribed meetings.
Build a multi-meeting AI chat interface where users can ask questions about any past meeting or search across all transcripts. Implement text chunking and vector embeddings using turso/libSQL vector search extensions (or simple SQLite full-text search if vector extension is unavailable) to retrieve relevant meeting context, pass it into an LLM prompt with system instructions, and stream the response back to the frontend UI.
Cost vs paying for Bluedot
What will you build it with?
Starting total with Claude Code$0 one-time
Starting costs (one-time)
- AI Coding Assistant subscription$20
- Domain name (optional)$12
Total~$32 one-time
Ongoing costs (monthly)
- OpenAI Whisper & LLM API usage~$5-15/mo depending on meeting volume
- Cloudflare R2 & Vercel hosting$0-5/mo
Total~$5-20/mo
Paying for Bluedot
$20/mo (Pro Plan)
Your time to build
30-40 hours
AI tool credits
$20 (Claude Code / Cursor Pro)
Break-even
1 month of heavy transcription usage
Vibe code Bluedot: FAQ
- Can you vibe code Bluedot yourself?
- Solid side project — 62/100 vibecodeable. Build a personal web-based audio upload and transcription dashboard, but skip writing native cross-platform desktop shells and browser extensions.
- How long does it take to vibe code Bluedot?
- 3-4 weeks of focused coding — roughly 30-40 hours of hands-on time with an AI coding agent.
- How do you build your own Bluedot?
- Scoped to personal use: Next.js with Tailwind CSS and shadcn/ui on the front, Next.js Server Actions and API Routes behind it, Turso (SQLite at the edge with vector support via libSQL) for data. Follow the 5-step build guide on this page — each step has a paste-ready prompt for an AI coding agent.
- How do you code your own Bluedot without being an expert?
- Use an AI coding tool (Claude Code or Cursor) and work in small steps: scaffold, data model, core screens, then deploy. Realistic effort: 3-4 weeks of focused coding. The prompts on this page are written so the AI does the heavy lifting.
- How much does it cost to vibe code Bluedot instead of paying?
- About ~$32 one-time to start and ~$5-20/mo to run, versus $20/mo (Pro Plan) for Bluedot. Break-even: 1 month of heavy transcription usage.
- What stack should you use to vibe code Bluedot?
- Next.js with Tailwind CSS and shadcn/ui; Next.js Server Actions and API Routes; Turso (SQLite at the edge with vector support via libSQL); plus OpenAI API (Whisper STT & GPT-4o), Cloudflare R2 (Audio/Video storage).