AI Tooling
Recruiter Automation
A free, browser-based tool that runs an LLM locally to rank resumes and chat about candidates — processing up to 1,000 files entirely offline, with no backend or API keys.
Recruiter Automation is a fully client-side recruiting tool that streamlines candidate screening directly in the browser. You define a job profile — title, seniority, years of experience, must-have and nice-to-have skills, and a pasted job description — then bulk-upload up to 1,000 PDF or DOCX resumes. The tool extracts skills, location, and experience from each document and ranks every candidate against the role. It is completely free, with no backend, API keys, or subscriptions.
- Define rich job profiles with weighted must-have / nice-to-have skills
- Bulk upload of up to 1,000 PDF/DOCX resumes
- Two-tier scoring: rule-based matching plus on-device AI reasoning
- Natural-language chat to ask questions about the candidate pool
- Installable PWA that works fully offline
On-device AI — nothing leaves your machine
The standout is that the AI runs entirely in the browser. On first use the app downloads and caches two models for offline use: a Phi-3.5 Mini LLM (~2.2 GB) for deep analysis and chat, and a GTE-small embedding model (~33 MB) for semantic resume matching, accelerated with WebGPU where available. All candidate data lives locally in IndexedDB and heavy parsing is offloaded to Web Workers via pdf.js and mammoth.js, so no resume ever leaves the user’s device. The frontend is a Vite-powered React + TypeScript stack styled with shadcn/ui and Tailwind CSS.