LLM-Driven Data Extraction
Arachnomancer powers this lab build: an autonomous crawler factory that turns a seed URL and schema sketch into a typed scraper in under an hour.
It discovers the right pages, narrows the HTML to what matters, and lets LLMs propose the structure before we lock everything back into deterministic selectors your team can own.
What teams get
- Schema-first delivery. You define the fields you need and receive production Scrapy projects that emit JSON or CSV straight into your pipeline.
- Repeatable launches. Cached plans, reusable primitives, and simulated runs keep new collectors shipping in minutes instead of weeks.
- Operational guardrails. Generative tests and proxy-aware fetchers catch anti-bot traps and schema drift before anything hits production.
Inside the pipeline
- Target discovery. We triage every link off the seed domain, score the ones that look like real items, and learn navigation patterns automatically.
- Signal isolation. Shared boilerplate is stripped away, then an LLM proposes candidate fields and example values for the item pages we keep.
- Selector synthesis. Deterministic XPath and JSON selectors are mined from those examples, validated with automated scoring, and packaged as code you can extend.
Why it matters
Teams collecting market or compliance data can stand up new crawlers on demand with deterministic code they can own and extend.
Want to talk through the architecture or adapt it to your domain?