The Work
Technical SEO for a global enterprise site (enormous, multilingual, constantly changing) can't be done by hand. So I stopped doing it by hand: I build agent-driven audit systems that run technical audits and recommendations continuously instead of waiting for a quarterly review. That approach is behind the 90% operational-efficiency gain in my enterprise SEO work.
That's the pattern across my technical work: find the repetitive expert task, then build the system that does it. The same builder mentality produced the crawl and entity infrastructure in my 4ort lab: an API-first crawler that mapped 191,000+ ecommerce domains, a knowledge graph serving ~40M entities, and structured-data pipelines built in Python and TypeScript from the ground up.
Structured data is a particular focus. Not just schema for rich results, but entity layers designed for the machines that increasingly read the web: search crawlers, answer engines, and autonomous agents.
Capabilities
- Audit automation: agent-driven technical auditing and recommendations, running continuously instead of quarterly
- Structured data at scale: Schema.org / JSON-LD implementation across global templates, for search engines and AI consumers
- Crawl engineering: building crawlers and data pipelines (Python, async httpx) rather than just operating off-the-shelf tools
- Enterprise site architecture: crawlability, indexation control, and template optimization for massive multilingual sites
- SEO automation development: custom tooling in Python and TypeScript, integrated with APIs and data flows
- Platform partnership: working directly with IT and engineering to ship technical SEO at the platform level