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

> Advanced SEO performance and AI visibility monitoring platform

- Site: https://nightwatch.io
- Category: SEO & AI Visibility SaaS
- Verdict: **Serious undertaking** (35/100 vibecodeable)
- Estimated effort: 3-4 months of part-time work

## Verdict

Build a simplified keyword and LLM citation tracker subset for personal use, but keep paying for the real product if you need enterprise-scale proxy infrastructure and 107,000-location precision.

Replicating Nightwatch as a solo developer hits a massive engineering wall at the scraping and proxy layer. While you can easily build the dashboard UI and orchestrate LLM prompts via APIs to track ChatGPT and Claude mentions, fetching search engine results across 107,000 zip codes daily without getting blocked by Google requires managing rotating residential proxy pools, handling complex CAPTCHAs, and maintaining raw HTML snapshot storage at scale. For personal use, you can scope down to a personal keyword tracker using headless browsers and structured LLM queries, but building production-grade SERP scraping infrastructure is a full-time engineering enterprise.

### What you can't replicate

- Proprietary global data centers with direct unblocked access to search engine indexes
- Guaranteed 99.9% rank-tracking accuracy backed by 3-year raw HTML snapshot archives across 107,000+ zip codes
- Enterprise-grade SLA support and native Looker Studio connectors

## What it does

Tracks traditional search engine rankings down to zip-code levels and uniquely unifies them with Citation Intelligence—an AI visibility layer tracking brand mentions across major LLMs and AI search engines.

### Core features

- Multi-engine rank tracking (Google, Bing, YouTube, Yahoo, DuckDuckGo)
- Zip-code level hyper-local tracking across 107,000+ locations
- Citation Intelligence: LLM visibility & mention tracking (ChatGPT, Claude, Gemini, Perplexity)
- Raw HTML SERP snapshot archiving for data verification
- Automated technical site auditing and page crawling
- White-label client reporting and custom PDF generation
- Keyword clustering, gap analysis, and content opportunity recommendations
- REST API and MCP server integration for AI assistants

## The business

### Pricing

- Starter: €79/mo — For individuals and small sites
- Professional: €159/mo — For growing teams and agencies
- Agency: €399/mo — For teams and high-volume tracking

### Funding

$0 raised.

Founded 2016.
Team size: 10-50.

## The hard parts

- Large-scale SERP scraping infrastructure that bypasses aggressive anti-bot defenses without burning proxies
- Precise local zip-code parameter simulation across global data centers
- Orchestrating multi-model LLM prompts at scale to parse unstructured brand citations and sentiment
- Time-series data architecture storing millions of historical SERP snapshots and ranking evolutions efficiently

## How to vibe code Nightwatch

### Prerequisites

- Node.js (free): Runtime for Next.js web application and background ingestion workers
- GitHub (free): Source control and CI/CD deployment pipeline integration

### Recommended AI tools

- Claude Code: Best-in-class coding agent for scaffolding multi-file full-stack apps and background workers
- Cursor: AI code editor for refining dashboard UI components and charting views

### Stack

- Frontend: Next.js with Tailwind CSS and Recharts
- Backend: Next.js Server Actions & API Routes with BullMQ
- Database: Turso (SQLite at the edge)
- Auth: better-auth
- Payments: none
- Other: Vercel AI SDK, Firecrawl, Resend

### Hosting

- Vercel (Hosting Next.js web dashboard and API routes): $0/mo (Hobby tier)
- Fly.io (Running background worker containers for scheduled SERP and LLM citation checks): ~$5/mo

### Build guide

1. **Project Scaffolding & Database Schema** — Initialize the Next.js application with TypeScript, Tailwind CSS, Turso database connection, and better-auth user authentication.

```
Scaffold a new Next.js project with TypeScript, Tailwind CSS, and App Router. Set up Turso database client using `@libsql/client` and configure better-auth for single-user authentication. Create database tables for `websites`, `keywords`, `rankings` (with columns for position, search volume, raw HTML snapshot text, and recorded date), `ai_prompts`, and `ai_citations` (tracking model name, brand mentioned, sentiment, and response text). Ensure proper relational foreign keys and indexes on `keyword_id` and `website_id` for fast time-series queries.
```

2. **Dashboard Layout & Metrics Overview** — Build the core analytics dashboard featuring sparklines, position evolution charts, and pinned tracking items.

```
Build a responsive Next.js dashboard mimicking Nightwatch's dark/light interface using Tailwind CSS. Create a main overview page with summary cards for Average Position, Search Visibility, AI Visibility score, and Click Potential. Use Recharts to render position trend lines and historical sparklines. Implement a modular grid layout supporting pinned items, tag filtering, and date range pickers (7D, 30D, 3M, 1Y).
```

3. **SERP Scraping & Snapshot Engine** — Implement background workers using Firecrawl or headless scrapers to fetch search engine results and store raw HTML snapshots.

```
Implement a background worker module using BullMQ and Node.js that accepts target keywords and domains for Google and Bing. Integrate Firecrawl API or headless browser automation to fetch search engine results pages (SERPs) for specified locations. Parse ranking positions, store the complete raw HTML response in the `rankings.snapshot_html` column for auditing, and calculate the current ranking position. Handle rate limiting and retry backoff gracefully.
```

4. **Citation Intelligence & LLM Tracking** — Build the AI visibility layer that queries LLMs with specific prompts to check for brand mentions, sentiment, and citations.

```
Create an AI tracking module using the Vercel AI SDK to programmatically query OpenAI, Anthropic, and Perplexity APIs with user-defined prompt strings (e.g. 'best hotel booking site'). Send structured system prompts asking the model to evaluate the top recommended brands, check if our target domain is cited or recommended, and output JSON containing `mentioned: boolean`, `sentiment: 'positive'|'neutral'|'negative'`, and `share_of_voice_percentage`. Store results in `ai_citations` and link them to corresponding keyword visibility data.
```

5. **Reporting & REST API Integration** — Develop white-label PDF report generation and a developer-friendly REST API for exporting tracking metrics.

```
Build a white-label reporting interface where users can customize report logos, colors, and metrics blocks, and export them as clean PDF summaries using `react-pdf`. Additionally, implement a secure REST API route protected by API keys (`/api/v1/rankings` and `/api/v1/ai-visibility`) allowing external tools or MCP clients to query keyword positions and citation history programmatically.
```

### Cost vs paying

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

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

**Ongoing costs (monthly):**

- Fly.io background workers: $5/mo
- LLM & Scraping API credits: ~$10/mo
- Total: ~$15/mo

- Paying for the SaaS instead: €79/mo (Starter) to €159/mo (Professional)
- Build time: 40-60 hours
- AI tool credits: $20 (Claude Code / Cursor Pro)
- Break-even: Depends on scale; built for personal utility rather than cost savings

## Sources

- [Nightwatch Official Website & Pricing Pages](https://nightwatch.io)
- [Ibrahim Furkan Ozcelik - AI Search Visibility Tools Comparison Guide (2026)](https://ibrahimfurkanozcelik.com)
- [Tracxn Company Profile - Nightwatch (2026)](https://tracxn.com)