Crawl

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Overview
AI-Optimized Blog Posts
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Rankings Page
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Inspiration

A close friend of ours, started an SEO/GEO agency and eventually exited it. That story was a huge inspiration for us. It made us wonder: what if the entire SEO/GEO workflow could be automated?

That idea became OpenClaw --> an AI-native SEO agency in a box. Even though SEO tools are a crowded space, we believe there’s still room to rethink how the whole pipeline works when AI agents handle most of the execution.

Our friend is currently building at Clover Labs but always thinking about the next big thing. We wanted to build something that carries that same builder spirit forward.

What it does

Crawl runs your SEO and GEO automatically.

It connects to your Google Search Console to track search rankings, uses AI to identify keyword gaps, and measures how often AI tools like ChatGPT, Perplexity, and Gemini cite your content.

The platform includes:

A dashboard for keywords, rankings, and GEO scores
AI-generated blog posts driven by keyword data
Automated reporting via Discord or Slack
Continuous monitoring of AI citations and search performance

The idea is simple: set it up once, then let it run.

How we built it

The stack combines a modern web app with an AI agent backend:

Frontend

Next.js dashboard
TipTap editor
Recharts + TanStack for data visualization

Backend

Supabase for authentication and database
Python agent system using FastAPI + LangChain/LangGraph

Infrastructure

BullMQ + Redis for background job queues
Google APIs for Analytics and Search Console
Gemini for AI generation

Everything lives in a Turborepo monorepo, allowing the web app and shared services to stay synchronized.

Challenges we ran into

One of the biggest challenges was getting the OpenClaw architecture working reliably.

We also ran into a lot of friction setting up Google Cloud and Search Console integrations. Permissions, API quotas, and authentication flows required quite a bit of iteration before everything worked smoothly.

Making all the moving pieces; crawling, keyword analysis, GEO scoring, content generation, and reporting --> work together in a stable pipeline was another major challenge.

Accomplishments that we're proud of

We’re especially proud that the frontend feels clean and intuitive despite the complexity behind the scenes.

Other highlights include:

Keeping token usage low so the system stays cost-efficient
Building a fully connected pipeline from
crawl → keyword discovery → GEO analysis → AI blog generation → reporting
Implementing Discord webhook notifications
Creating an AI agent audit system to track what the automation is doing internally

Seeing the entire system run end-to-end was a big milestone for us.