ApplyPass

ApplyPass is the AI-powered career accelerator that automates your entire job search. Its advanced engine tailors your résumé, scours 60 k live openings, and submits applications while you focus on interview prep. Users report 40 % higher recruiter response rates and land offers in as little as 38 days.

Employer-Grade Parsing
ApplyPass begins by ingesting a user’s résumé and LinkedIn URL through a privacy-first parser that maps skills, seniority, and domain keywords to a proprietary taxonomy of 1.2 million job titles. The parser is built on a fine-tuned BERT model that outperforms off-the-shelf ATS parsers by 18 % on a F1-score benchmark created from 50,000 real-world résumés.

Dynamic Job Graph
Rather than scraping public boards, ApplyPass maintains a live graph of 60,000+ companies updated via direct API integrations with Greenhouse, Lever, Workday, and BambooHR. Graph edges represent nuanced requirements such as “remote OK,” “sponsorship available,” or “security clearance required.” A GNN (Graph Neural Network) ranks opportunities in real time based on 38 weighted signals—skill overlap, commute radius, company growth stage, and recruiter response latency among them.

Hyper-Personalized Tailoring
Once a high-fit role is identified, a fine-tuned Llama-3 70-B parameter model rewrites the top third of the résumé and cover letter to mirror the posting’s diction while preserving factual integrity. A/B tests show this step alone lifts recruiter open rates from 9 % to 14 %. The model also injects missing ATS keywords that gatekeeper systems like Taleo or iCIMS scan for.