# How to Vibe Code Your Own Fireflies.ai (and Stop Paying for It)

> AI Assistant for Meetings, Email, Chat & CRM

- Site: https://fireflies.ai
- Category: Productivity & AI
- Verdict: **Solid side project** (62/100 vibecodeable)
- Estimated effort: 3-4 weeks of focused development

## Verdict

You can build a personal meeting transcriber and summarizer for your own audio uploads or Google Meet recordings, but reliable multi-platform automated bot dialing is a maintenance nightmare.

Building a personal-use clone of Fireflies is a rewarding undertaking if you scope it correctly. Instead of trying to orchestrate headless browser bots to sneak into Zoom, Teams, and Google Meet meetings (which breaks constantly when video providers update their DOM or lobby policies), a sensible personal clone should ingest recorded audio files (MP3/WAV) or use a browser extension for direct tab capture. From there, you hook into the OpenAI API for Whisper transcription and Claude/GPT models for meeting summaries, action items, and vector search over past transcripts. You will spend most of your debugging time tuning prompt structures and handling audio chunk uploads rather than building complex UI.

### What you can't replicate

- Bulletproof, self-healing headless bots that bypass modern video conferencing security and lobby walls across Zoom, Teams, and Webex
- Native enterprise compliance certifications (HIPAA BAA, SOC 2 Type II)
- Pre-built native integrations with dozens of enterprise CRMs and ATS platforms

## What it does

An AI-powered meeting assistant that automatically joins video conferences, records audio, transcribes speech, generates concise AI summaries, and provides conversational search.

### Core features

- Calendar integration and automated meeting bot joining
- Audio recording and multi-language speech-to-text transcription
- Speaker diarization and talk-time analytics
- LLM-powered meeting summaries and action item extraction
- Conversational search interface (AskFred) over meeting archives
- Task and CRM export integrations

## The business

### Pricing

- Free: $0 / forever
- Pro: $10/mo billed annually ($18/mo monthly)
- Business: $19/mo billed annually ($29/mo monthly)
- Enterprise: $39/mo billed annually

### Funding

$19.1M raised.
- Pre-Seed / Seed (~$4.9M)
- Series A ($14M led by Khosla Ventures)
Investors: Khosla Ventures, Canaan Partners

Founded 2016.
Team size: 100-126.

## The hard parts

- The Bot Orchestration Problem: reliably spinning Headless Chrome or WebRTC bot instances to dial into Zoom, Teams, and Google Meet without breaking on lobby permissions or UI changes.
- Real-Time Audio Stream Processing: splitting multi-speaker audio tracks (diarization) cleanly with high precision across 100+ languages.
- Enterprise Compliance: enforcing strict SOC 2, GDPR, and HIPAA data isolation and encryption standards.

## How to vibe code Fireflies.ai

### Prerequisites

- Node.js (free): Runtime environment for the Next.js full-stack application.
- GitHub (free): Source control and deployment pipeline connector for Vercel.
- OpenAI API Key (Pay-as-you-go (~$0.006/min)): Required for Whisper speech-to-text audio transcription.

### Recommended AI tools

- Cursor: The best AI code editor for rapidly scaffolding UI components and iterating on full-stack codebases.
- Claude Code: Excellent terminal agent for handling multi-file backend logic, database schema design, and complex debugging loops.

### Stack

- Frontend: Next.js with Tailwind CSS and shadcn/ui
- Backend: Next.js Server Actions and API Routes
- Database: Neon (Serverless Postgres with pgvector for transcript search)
- Auth: better-auth
- Payments: none (personal use clone)
- Other: OpenAI API (Whisper & GPT-4o), UploadThing (audio file uploads)

### Hosting

- Vercel (Hosting the Next.js frontend, API endpoints, and serverless functions): $0-20/mo
- Neon (Serverless Postgres database with vector search capabilities for transcripts): $0/mo

### Build guide

1. **Project Scaffolding & Database Schema** — Initialize a Next.js project with Tailwind CSS and shadcn/ui. Configure Neon Postgres with Drizzle ORM to handle users, meetings, transcripts, and vector embeddings.

```
Scaffold a new Next.js 16 application with TypeScript, Tailwind CSS, and App Router. Set up Drizzle ORM connected to a Neon Postgres database. Define database schemas for 'users', 'meetings' (id, userId, title, audioUrl, duration, createdAt), 'transcripts' (id, meetingId, speaker, text, startTime, endTime), and 'summaries' (id, meetingId, bulletPoints, actionItems, embedding vector). Include pgvector extension initialization in the migration scripts.
```

2. **Authentication Setup** — Implement local authentication using better-auth to secure the personal dashboard and manage user sessions.

```
Integrate 'better-auth' into the Next.js application using the Neon Postgres database adapter. Create email/password sign-in and sign-up pages with clean Tailwind CSS styling. Add middleware to protect dashboard routes and ensure users can only access their own meeting records.
```

3. **Audio Upload & Whisper Transcription Pipeline** — Build an audio file upload widget using UploadThing and connect it to a background processing action that transcribes audio via the OpenAI Whisper API.

```
Create a file upload component using UploadThing that accepts MP3, WAV, and M4A audio files up to 500MB. When an upload completes, trigger a server action that downloads the file temporarily or streams it to the OpenAI Whisper API (v1 /audio/transcriptions) with timestamp granularity. Store the resulting transcript chunks with speaker segments and start/end times into the 'transcripts' table.
```

4. **AI Summarization & Action Item Extraction** — Implement an LLM processing step that analyzes completed transcripts to generate structured summaries, executive bullet points, and actionable tasks.

```
Write a server-side utility function that compiles a meeting transcript from database records and sends it to the OpenAI or Anthropic API with a structured prompt. Instruct the model to return a JSON object containing an executive summary, key bullet points, and a list of action items with assignees. Save these outputs into the 'summaries' table and display them in a clean dashboard view.
```

5. **AskFred Conversational Search Interface** — Build a conversational RAG interface allowing users to ask questions about past meeting contents using pgvector semantic search.

```
Build an 'AskFred' chat interface UI in the dashboard. When a user submits a query, generate an embedding of the question, query the 'transcripts' table using Neon pgvector cosine similarity to retrieve relevant transcript snippets, and feed those snippets into an LLM context window. Return an accurate, grounded answer with citations pointing to specific meeting timestamps.
```

6. **Dashboard UI & Audio Player Integration** — Develop the main meeting dashboard with searchable history, detailed transcript views, and an audio waveform player synced to transcript timestamps.

```
Create a responsive dashboard page displaying a list of recorded meetings with search and filter capabilities. Build a detail view for a single meeting that includes an audio player, a scrolling transcript view where clicking a transcript segment jumps the audio playback to that exact timestamp, and tabs for summary, action items, and chat.
```

### Cost vs paying

**Starting costs (one-time):**

- Domain name (optional): $12/yr
- Total: ~$12 one-time

**Ongoing costs (monthly):**

- OpenAI Whisper & LLM API usage: ~$5-15/mo depending on meeting volume
- Vercel & Neon hosting: $0/mo (Free tiers)
- Total: ~$10/mo

- Paying for the SaaS instead: $19/mo (Business Tier)
- Build time: 25-35 hours
- AI tool credits: $20 (Cursor Pro)
- Break-even: N/A (Built for personal utility and learning)

## Sources

- [Fireflies.ai Official Website & Feature Pages](https://fireflies.ai)
- [Crunchbase News - June Unicorn Births & Fireflies Valuation](https://www.crunchbase.com)
- [GetLatka - Fireflies.ai Revenue and Financial Growth Estimates](https://getlatka.com)