PH Deck

Users manually search multiple job boards for relevant roles, leading to stale listings and hopping across job sites, which is time-consuming and inefficient.

Job seekers face inefficiencies in traditional job searching methods, such as manually tracking applications and preparing for interviews without AI assistance. Time-consuming application tracking and lack of personalized interview feedback reduce their chances of success.

Job seekers often struggle to find relevant job opportunities, tailor resumes and cover letters for each position, and prepare effectively for interviews, leading to inefficient job search processes and missed opportunities. Struggle to find relevant job opportunities and tailor resumes

Users manually search and apply for jobs by browsing multiple portals and tweaking resumes for each application. Manually searching and applying for jobs, tweaking resumes for each application

Users struggle with manually creating and maintaining personalized habits and face ineffective reminders that lead to inconsistent routines.

Job seekers manually tailor each application to match job descriptions, which is time-consuming and often ineffective due to generic content and misalignment with employer requirements.

Users seeking astrological guidance traditionally rely on manual consultations or generic horoscope apps, which lack personalization and real-time interaction.

Users struggle with manually tailoring each resume for different job applications, leading to a time-consuming and error-prone process that reduces their chances of passing applicant tracking systems (ATS) and securing interviews.

Currently, fitness enthusiasts often rely on traditional workout plans and logging methods that are time-intensive and lack personalized guidance. These methods often involve manually tracking workouts, researching exercises suited to individual needs, and regularly updating plans. The drawbacks of this old situation include: time-intensive manual logging, limited personalization, and lack of adaptive guidance based on progress.

Users need to create multiple personalized videos for individual viewers, which is time-consuming and resource-intensive.

Drawbacks: Manual customization of videos for each viewer results in high production costs, time constraints, and difficulty in achieving scalability.