AI portfolio builder that creates project-focused portfolios from descriptions
Denetor is an AI tool that generates professional portfolios focused on projects, not personal websites. Users describe their work and the AI structures it to highlight what was built, why it matters, problems solved, and impact created. It solves the problem of time-consuming portfolio curation for professionals.
Visit project ↗Related
AI-powered freelancer proposal tool built via AI-driven problem discovery
A tool that helps freelancers write better proposals by using a multi-step AI framework to identify and solve real freelancing problems. The creator used a 13-16 step process with multiple AIs to discover the problem and build a prompt-based solution, without personal freelancing experience.
CV AI: AI-powered CV generator that creates polished PDFs in under 60 seconds
CV AI is a web tool that uses an LLM to generate clean, professional CVs as PDFs in under a minute. It solves the problem of messy Word templates and time-consuming design tools for job seekers who want a quick, no-frills resume. The creator built it in 24 hours using 'vibe coding' and has had 9 users test it.
AI-powered job search tool that scores and recommends top jobs
A web tool that queries multiple job APIs, filters and scores listings against a user's career profile using AI, then sends the top 5 matches. It helps job seekers find relevant opportunities efficiently.
All-in-one workspace to tailor resumes to job descriptions
ApplyBoost is a web app that consolidates the resume tailoring workflow into a single workspace. It uses LLMs to rewrite bullet points, identify missing keywords, and scan for ATS compatibility, helping job seekers save time and improve their applications.
PortLume AI: career-long agent that diagnoses interview failures and builds your profile
PortLume AI is an AI agent that accompanies users throughout their career, not just during job searches. It builds a detailed profile over time, documents experience, and after an interview, analyzes what went wrong stage-by-stage, providing actionable fixes. It uses LLMs to understand user input and generate personalized feedback.