# How to Vibe Code Your Own DeleteMe (and Stop Paying for It) > Remove Personal Data from Internet & Data Brokers - Site: https://joindeleteme.com - Category: Privacy & Security SaaS - Verdict: **Serious undertaking** (35/100 vibecodeable) - Estimated effort: 6+ months of part-time development and ongoing maintenance ## Verdict You can build the user dashboard and a basic automated scraper in a few weekends, but you cannot replicate the massive human operations team required to force 750+ uncooperative data brokers to comply. Building a personal clone of DeleteMe's SaaS dashboard and scraping pipeline is a rewarding challenge, but the core product value relies on a relentless human-in-the-loop operations engine. While AI can easily scaffold the Next.js frontend, database schemas, and Python scrapers using Firecrawl or Playwright, you will hit a brick wall when data brokers introduce CAPTCHAs, require phone verification, or simply ignore automated opt-out forms. Unless you plan to manually process hundreds of removal requests yourself every month, the automation will only cover a fraction of what a paid subscription delivers. ### What you can't replicate - The dedicated operations team of privacy advisors handling manual broker paperwork and disputes - Institutional database of hundreds of bespoke, constantly-breaking data broker scraping parsers - Enterprise trust, compliance certifications, and legal standing against abusive brokers ## What it does A consumer and enterprise privacy service that removes personal identifiable information from online data brokers and people-search directories through automated and manual operations. ### Core features - User profile & PII data collection (names, aliases, addresses, phones, emails) - Dashboard for monitoring removal progress and exposed listings - Automated scanning and scraping pipeline against data broker targets - Opt-out request submission queue (API and form submissions) - Customer reporting and notification system (weekly/monthly summaries) - Admin panel for managing broker definitions and manual overrides ## The business ### Pricing - 1 Person (1 Year): $129.50/yr — Covers 1 individual with continuous monitoring and annual commitment. - 2 People (1 Year): $229.50/yr — Most popular plan for couples or pairs. - Family / 4 People (1 Year): $349.50/yr — Comprehensive coverage for households. Founded 2010. Team size: 50–200. ## The hard parts - Data broker DOM changes and anti-bot measures (CAPTCHAs, rate limits) across hundreds of targets - Handling identity verification hurdles (email verifications, SMS codes, or mail-in opt-outs) - The human-in-the-loop operational scaling required to handle brokers who refuse automated compliance - Maintaining robust scrapers and parsers as data broker layouts shift constantly ## How to vibe code DeleteMe ### Prerequisites - Node.js (free): Required for running the Next.js full-stack web application. - Python (free): Required for building the web scraping and broker opt-out automation scripts. - GitHub (free): Version control and CI/CD deployment pipelines. ### Recommended AI tools - Cursor: Ideal for iterative frontend UI work and managing the Next.js codebase with inline diff reviews. - Claude Code: Exceptional terminal coding agent for scaffolding complex backend data pipelines and database models. ### Stack - Frontend: Next.js with Tailwind CSS and shadcn/ui - Backend: Next.js API routes & Python worker scripts - Database: Supabase (PostgreSQL with pgvector for data matching) - Auth: better-auth - Payments: Stripe - Other: Firecrawl for web scraping research, Playwright for browser automation opt-outs ### Hosting - Vercel (Hosting the Next.js web application frontend and dashboard API routes.): $0-20/mo - Railway (Hosting background Python scraping workers and automated opt-out job queues.): ~$5-10/mo - Supabase (Managing user profiles, PII targets, and broker exposure tracking records.): $0/mo (Free tier) ### Build guide 1. **Project Setup & Database Schema** — Initialize the Next.js project with Tailwind CSS and configure Supabase with better-auth. Set up tables for user profiles, aliases, monitored PII fields (names, addresses, phone numbers, emails), and data broker exposure records. ``` Initialize a new Next.js project with TypeScript, Tailwind CSS, and App Router. Set up better-auth with email/password authentication connected to Supabase PostgreSQL. Create database migrations and Prisma/Drizzle schemas for users, user_profiles (storing names, previous names, aliases, addresses, phone numbers, emails), broker_targets (list of data brokers with URLs and status), and exposure_records (linking user profiles to broker targets with statuses like 'exposed', 'removal_requested', 'removed'). Implement a clean dashboard layout using shadcn/ui components. ``` 2. **User Profile & PII Management Dashboard** — Build the customer onboarding flow where users input their personal identifying information to be scanned and monitored. ``` Build a multi-step onboarding wizard in Next.js where users input their current name, previous names, aliases, current and past physical addresses, phone numbers, and email addresses. Store these securely in the user_profiles table with encryption at rest considerations. Create a dashboard view that displays summary metrics: total exposures found, active removal requests, and clean status across scanned data brokers. Include a settings page to update or add new PII details as life events occur. ``` 3. **Data Broker Exposure Scanning Engine** — Develop a Python-based worker service using Playwright and Firecrawl to search and parse data broker directories for user PII. ``` Create a Python microservice using Playwright and BeautifulSoup (or Firecrawl API) designed to query mock data broker search pages using a user's name, city, and state. Implement an LLM-powered extraction parser using the Gemini API to parse search results HTML and determine if a returned profile matches the user's specific PII (matching name, address, or phone). Store matched exposure records in the Supabase database with confidence scores and source URLs. ``` 4. **Automated Opt-Out Submission Queue** — Implement background job handlers that automate form submissions or email opt-outs for discovered broker listings. ``` Build a background worker queue in Python/Railway that processes 'exposed' records by executing automated opt-out routines. For simple brokers, write Playwright automation scripts to fill out web opt-out forms, solve basic captcha prompts or trigger email verification links. For brokers requiring manual intervention, flag the record as 'needs_human_review' and assign it to an internal admin queue. Log all submission attempts and timestamps in an audit log table. ``` 5. **Admin Operations & Human-in-the-Loop Review Panel** — Construct an internal admin dashboard for reviewing flagged broker removal failures and verifying manual completions. ``` Create an admin-only route group in Next.js (`/admin`) protected by role-based auth. Build a review queue interface where operators can view pending data broker removal requests, inspect screenshots of broker pages captured by Playwright, and manually mark listings as 'removed' or 'disputed'. Include batch actions and operator activity logs to track throughput on manual opt-out submissions. ``` 6. **Subscription Billing & Notifications** — Integrate Stripe for recurring subscription plans and Resend for transactional exposure progress updates. ``` Integrate Stripe billing into the Next.js application supporting annual and multi-year subscription plans for individuals and families. Set up webhook handlers to update user subscription tiers and expiration dates in the database. Integrate Resend to automatically dispatch weekly or monthly email digest reports summarizing new exposures found, removals completed, and ongoing privacy protection stats using clean HTML email templates. ``` ### Cost vs paying **Starting costs (one-time):** - Domain registration: ~$12 one-time - AI coding agent credits: ~$20 one-time - Total: ~$32 one-time **Ongoing costs (monthly):** - Vercel Hobby / Pro Hosting: $0-20/mo - Railway Python Workers: ~$5-10/mo - Supabase Database: $0/mo - Total: ~$5-30/mo - Paying for the SaaS instead: ~$10.79/mo to $29.13/mo (depending on plan) - Build time: 120-160 hours - AI tool credits: $20/mo (Cursor/Claude Pro) - Break-even: Self-hosting only makes sense for learning; paying for the commercial service is vastly cheaper when accounting for the thousands of hours required to maintain broker scrapers. ## Sources - [DeleteMe Official Website](https://joindeleteme.com) - [DeleteMe Pricing Page](https://joindeleteme.com/plans) - [DeleteMe Business Pricing](https://joindeleteme.com/business/pricing) - [DeleteMe About Us Page](https://joindeleteme.com/about-us) - [DeleteMe Security Overview](https://joindeleteme.com/security)