The verdict: can you vibe code Recall?
Build a solid personal subset of Recall with a Next.js web app and browser extension, but expect friction when wiring robust background media ingestion pipelines.
Cloning Recall for personal use is an ambitious solid side project. While the core UI (Next.js, Tailwind CSS, a block editor, and a force graph component) can be spun up quickly with AI coding tools, the real engineering weight lies in asynchronous media processing. Ingesting, chunking, and transcribing multi-hour YouTube videos and large PDFs without timing out serverless functions requires dedicated background job runners like Trigger.dev and careful database design with pgvector in Neon. Furthermore, maintaining parity with their browser extension and local-first augmented browsing introduces significant extension manifest and CORS complexity.
Estimated effort: 3-4 weeks of part-time development
What you can't replicate
- The exact 500,000+ user community and organic acquisition loops
- Proprietary enterprise onboarding infrastructure and multi-year data history
Founded
2022
Raised
$1.5M
Team
3 core founders
Cheapest paid tier
$0
What Recall does
An AI-powered personal knowledge base and second brain application that saves, summarizes, organizes, and lets you chat with content from across the web, including YouTube videos, podcasts, PDFs, and personal notes.
Core features
- One-click browser extension content saver for articles, YouTube videos, and PDFs
- Automated multi-media transcription and summarization with timestamps
- Vector embeddings and pgvector storage for semantic search and RAG
- Automated smart-tagging and concept entity extraction
- Interactive visual knowledge graph showing relationships between cards
- Multi-model AI chat (OpenAI, Anthropic, Gemini) with knowledge grounding
- Spaced repetition quiz generator and review schedule
- Notion-style block editor for personal notes
The business
Pricing
- Free$0
- Plus$10/mo
- Max$38/mo
Funding
$1.5M from Jason Calacanis / LAUNCH Accelerator, Splash Capital, Blockchain Founders Capital, Rocket Capital
Pay vs build, cumulative
No break-even inside 24 months at these numbers.
The hard parts of vibe coding Recall
- Robust background ingestion queues that can fetch, parse, and transcribe massive inputs (such as 10-hour YouTube videos or 300-page PDFs) without hitting API limits
- Automated concept extraction and graph linkage pipeline that maps semantic relationships between unstructured notes and media sources
- Local-first augmented browsing architecture that safely resurfaces relevant past knowledge as you browse the open web
- Multi-model provider orchestration allowing seamless context switching across diverse LLM APIs
How to vibecode Recall
Prerequisites
Node.jsfree
Required runtime for Next.js development and package management
GitHubfree
Repository hosting and continuous deployment integration
OpenAI / Anthropic API Keyspay-as-you-go
Provides LLM reasoning, embeddings, and transcription models for processing saved content
AI coding tools
Recommended stack
| Frontend | Next.js with Tailwind CSS and shadcn/ui |
|---|---|
| Backend | Next.js Server Actions and API Routes with Trigger.dev for background jobs |
| Database | Neon (Serverless Postgres with pgvector) |
| Auth | better-auth |
| Payments | none |
| Other | Vercel AI SDK, Firecrawl |
Build guide
01Project Scaffolding & Database Schema
Initialize the Next.js repository with Tailwind CSS, shadcn/ui, and better-auth connected to a Neon Postgres database configured with pgvector.
Scrape or set up a fresh Next.js project using App Router, Tailwind CSS, and TypeScript. Configure better-auth for single-user authentication with email/password. Connect the app to a Neon Postgres database using Drizzle ORM or Prisma. Create database tables for users, recall_cards (storing title, url, raw_content, summary, content_type, and embedding vector via pgvector), tags, and card_relations. Ensure the migration files are properly structured and test the local development server starts without errors.02Content Ingestion & Scraping Pipeline
Build backend extraction endpoints that take URLs, PDFs, or YouTube links, extract text using Firecrawl or platform APIs, and store raw content.
Build a robust API route in Next.js that accepts a URL or uploaded file (PDF, text note). Integrate Firecrawl API for web page scraping and use OpenAI Whisper or direct text extraction for PDFs and YouTube transcripts. Implement error handling for rate limits, payload size limits, and invalid URLs. Save the extracted clean text into the recall_cards table in Neon with a status of 'pending_summary'.03AI Summarization & Smart Tagging Engine
Implement background processing tasks that generate structured summaries, timestamped notes, and smart tags using the Vercel AI SDK.
Implement an asynchronous background processing function using Trigger.dev or a serverless queue that picks up newly saved recall_cards. Using the Vercel AI SDK and Anthropic Claude or OpenAI models, generate a structured JSON object containing a concise summary, timestamped key points, and smart tags. Compute text embeddings for the summary using OpenAI's embedding model and store them in the pgvector column. Update the card status to 'completed'.04Knowledge Graph & Visual Connections
Create an interactive knowledge graph visualization using D3.js or React Flow that links related cards based on vector similarity and shared tags.
Build a dedicated /graph page in the Next.js app featuring an interactive graph visualization using React Flow or D3.js. Query the database for recall_cards and their semantic relationships, calculated via vector distance in pgvector or shared smart tags. Render nodes representing cards and edges representing relationships, allowing users to click a node to view its summary and connected notes.05Multi-Model AI Chat & Search Interface
Build the central chat interface that retrieves relevant saved cards via vector search and allows querying across user knowledge or the open web.
Create a chat interface component using the Vercel AI SDK useChat hook. Implement a retrieval-augmented generation (RAG) backend query that searches the user's saved recall_cards using pgvector cosine similarity against the user's prompt. Allow users to select their preferred AI model (OpenAI, Anthropic, Gemini) from a dropdown switcher. Ensure chat responses cite specific saved Recall Cards as sources.06Spaced Repetition Quizzes & Polish
Add an active recall quiz generator that creates flashcards from saved summaries and schedules reviews using a spaced repetition algorithm.
Implement a spaced repetition review module. Create a backend action that prompts an LLM to generate 3-5 multiple-choice and short-answer quiz questions from a selected Recall Card summary. Store these in a quizzes table with review intervals and scheduling metadata. Build a review dashboard frontend that presents due cards, records user recall performance, and adjusts the next review timestamp accordingly.
Cost vs paying for Recall
What will you build it with?
Starting total with Claude Code$0 one-time
Starting costs (one-time)
- Domain name (optional)$12 one-time
- AI coding tool subscription$20 one-time
Total~$32 one-time
Ongoing costs (monthly)
- Vercel Hobby / Neon Postgres$0/mo
- OpenAI / Anthropic API usage for summaries & chat~$5-15/mo
Total~$5-15/mo
Paying for Recall
$10/mo (Plus) or $38/mo (Max)
Your time to build
30-40 hours
AI tool credits
$20 one-time (Claude Pro / Cursor)
Break-even
N/A (Built for personal use and learning)
Vibe code Recall: FAQ
- Can you vibe code Recall yourself?
- Solid side project — 62/100 vibecodeable. Build a solid personal subset of Recall with a Next.js web app and browser extension, but expect friction when wiring robust background media ingestion pipelines.
- How long does it take to vibe code Recall?
- 3-4 weeks of part-time development — roughly 30-40 hours of hands-on time with an AI coding agent.
- How do you build your own Recall?
- Scoped to personal use: Next.js with Tailwind CSS and shadcn/ui on the front, Next.js Server Actions and API Routes with Trigger.dev for background jobs behind it, Neon (Serverless Postgres with pgvector) for data. Follow the 6-step build guide on this page — each step has a paste-ready prompt for an AI coding agent.
- How do you code your own Recall 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 part-time development. The prompts on this page are written so the AI does the heavy lifting.
- How much does it cost to vibe code Recall instead of paying?
- About ~$32 one-time to start and ~$5-15/mo to run, versus $10/mo (Plus) or $38/mo (Max) for Recall. Break-even: N/A (Built for personal use and learning).
- What stack should you use to vibe code Recall?
- Next.js with Tailwind CSS and shadcn/ui; Next.js Server Actions and API Routes with Trigger.dev for background jobs; Neon (Serverless Postgres with pgvector); plus Vercel AI SDK, Firecrawl.