# How to Vibe Code Your Own Riverside (and Stop Paying for It)

> All-in-one AI platform for remote podcasting, video interviews, and webinars

- Site: https://riverside.fm
- Category: Video & Audio Production SaaS
- Platforms: Web app, iOS app, Android app, macOS app
- Verdict: **Don't bother** (18/100 vibecodeable)
- Estimated effort: 6+ months of full-time work

## Verdict

Keep paying for Riverside unless you have a multi-year background in WebRTC and browser-native media streaming engineering.

Building a functional clone of Riverside's core differentiator—reliable client-side 4K local recording with multi-track sync over unstable web connections—is an extreme systems engineering challenge. Browser APIs like MediaRecorder and WebCodecs are notoriously fragile under heavy load, and managing raw video chunk buffering in IndexedDB while avoiding out-of-memory crashes requires expert-level frontend architecture. While you can build a basic wrapper around WebRTC video calls, replicating pristine uncompressed local recording and automated AI video editing makes this a dont_bother project for a solo developer.

### What you can't replicate

- Bulletproof client-side local recording engine that survives browser crashes and memory spikes
- Advanced multi-track clock-drift correction across remote participant machines
- Enterprise compliance framework (SOC2, ISO27001)

## What it does

Riverside provides local 4K video recording, uncompressed audio tracks, text-based video editing, AI transcriptions, magic clips, and live streaming tools.

### Core features

- Browser-based local multi-track recording using MediaRecorder and WebCodecs APIs
- Resilient background chunk uploads to object storage
- Multi-participant WebRTC signaling and real-time video preview grid
- Text-based video editor synchronizing transcripts with media timelines
- AI transcription, filler-word removal, and automated short clip generation
- Podcast hosting and RSS feed publishing

## The business

### Pricing

- Free: $0
- Pro: $29/mo
- Business: Custom

### Funding

$77M - $80M raised.
- Seed Round
- Series A ($9.5M)
- Series B ($35M)
- Series C ($30M)
Investors: Zeev Ventures, Seven Seven Six, Alexis Ohanian, Lachy Groom, Elad Gil

Founded 2019.
Team size: 201-500.

## The hard parts

- Client-side 4K video and raw audio capture without browser tab crashes or memory leaks
- Re-syncing separate local tracks in the cloud after long recording sessions with clock drift
- Coordinating low-latency WebRTC media streams across varying participant network conditions
- Processing compute-heavy AI tasks like transcription, automated clipping, and video dubbing at scale

## How to vibe code Riverside

### Prerequisites

- Node.js (free): Required runtime for the local development environment
- GitHub (free): Code repository hosting and version control

### Recommended AI tools

- Claude Code: Handles complex multi-file application scaffolding and debugging across the stack

### Stack

- Frontend: Next.js
- Backend: Next.js API routes with LiveKit for WebRTC
- Database: Turso
- Auth: better-auth
- Payments: Stripe
- Other: OpenAI API, Tailwind CSS, LiveKit

### Hosting

- Cloudflare (Edge hosting and R2 storage for recorded media chunks): $5/mo

### Build guide

1. **Project Scaffolding & Database Setup** — Initialize the Next.js project with Tailwind CSS, configure Turso database schema for studios, participants, and recordings, and set up better-auth.

```
Initialize a Next.js full-stack application using App Router, TypeScript, and Tailwind CSS. Configure better-auth with email/password authentication backed by a Turso SQLite database using the libSQL client. Create database tables for 'studios' (id, name, host_id, created_at), 'participants' (id, studio_id, name, role), and 'recordings' (id, studio_id, participant_id, file_url, duration, created_at). Set up clean error handling and environment validation.
```

2. **WebRTC Video Room Infrastructure** — Implement a real-time video conferencing room using LiveKit or custom WebRTC signaling for host and participant video previews.

```
Implement a video room component in Next.js using LiveKit components or WebRTC APIs. Create a studio dashboard page where a host can generate a unique invite link, and participants can join after granting camera and microphone permissions. Display a responsive grid of video tiles with mute/unmute audio and video toggle controls, connection status indicators, and active speaker highlighting.
```

3. **Client-Side Local Recording Pipeline** — Build the client-side MediaRecorder pipeline that records raw video and uncompressed audio locally into chunks stored in IndexedDB.

```
Build a client-side local recording manager using the MediaRecorder API and WebCodecs where supported. The system must capture raw video streams from the local camera and uncompressed audio tracks, buffering data chunks into IndexedDB in real time during the interview session to prevent data loss on network drops.
```

4. **Background Chunk Upload & Storage** — Implement resilient background chunk uploading from IndexedDB to Cloudflare R2 object storage with retry logic.

```
Implement a background upload queue in TypeScript that reads recorded chunks from IndexedDB and uploads them sequentially to Cloudflare R2 via presigned URLs. Include robust exponential backoff retry mechanisms for handling unstable internet connections, progress indicators for the user, and an API endpoint to finalize and merge chunks once the recording session ends.
```

5. **AI Transcription & Text-Based Editor** — Integrate OpenAI Whisper for audio transcription and build a text-based document editor interface for video trimming.

```
Create a text-based video editor interface in Next.js. Build an API route that sends completed audio tracks to the OpenAI Whisper API to generate a timestamped JSON transcript. Render the transcript as an interactive document where users can select and delete text blocks, which automatically updates the corresponding video timeline cut points for export.
```

### Cost vs paying

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

- Domain registration: $12
- Total: ~$12 one-time

**Ongoing costs (monthly):**

- Cloudflare Workers & R2 storage: $5/mo
- OpenAI Whisper & LLM API usage: $15/mo
- Total: ~$20/mo

- Paying for the SaaS instead: $29/mo
- Build time: 160+ hours
- AI tool credits: $20/mo
- Break-even: Never (subscription is cheaper than your engineering time)

## Sources

- [Riverside.fm Official Website](https://riverside.fm)
- [Wikipedia - Riverside (software)](https://en.wikipedia.org/wiki/Riverside_(software))