Professional work · Research system · AI
Window-profile research
A staged pipeline that researches window and door manufacturers and prepares profile-system data for WinFactor onboarding.
A browser-driving language-model agent reads each manufacturer site and returns the profile-system data as structured JSON.
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Research pipeline
- The pipeline scrapes manufacturer websites, refines systems into product lines, and assembles per-country JSON.
- Its source workbook lists 1,426 manufacturers across 43 countries.
- Each brand gets its own agent session. The agent drives a browser through an MCP server and extracts the fields of the profile-system schema.
- A validation step checks the returned JSON and resumes the same session to repair a rejected or malformed answer.
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Operation
- Docker workers run on two remote machines, with Tailscale for connectivity and a local coordination machine.
- The output follows the schema used by the WinFactor profile-system onboarding flow.
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