/ 01
Profile intelligence
Parse resumes, profiles and portfolio links into skills, experience, education, projects and preferred roles.
Project overview
An upcoming AI career project where contributors practice semantic search, AI workflow design, browser automation, application tracking, and cloud architecture.
Ascenjo is planned as a React, TypeScript, Tailwind and ShadCN web app for dashboards, job recommendations, resume workflows, application tracking and analytics.
A NestJS backend with Prisma, JWT and PostgreSQL powers profiles, jobs, resumes and applications. pgvector supports semantic matching between resume embeddings and job embeddings, while Redis handles cache, sessions, rate limiting and AI response caching.
The AI and agent layer uses OpenAI, Gemini or Claude for resume analysis, ATS optimization, cover letters and job scoring, with Playwright + Chromium browser agents for assisted job applications.
Parse resumes, profiles and portfolio links into skills, experience, education, projects and preferred roles.
Search and rank jobs from portals and career pages based on role, location, salary, visa needs and fit.
PostgreSQL with pgvector stores resume and job embeddings for meaning-aware job recommendations.
Generate ATS-optimized resumes and personalized cover letters for specific job descriptions.
Playwright and Chromium support assisted application workflows like filling forms and uploading resumes with user approval.
Track application status, interviews, offers and analytics from a single dashboard.
The contributors behind the build and the engineering areas they owned.
Leads AI workflow design, architecture discussions and the career automation learning path.
Owns backend architecture, APIs, database workflows and service integration.
Builds frontend flows, reliable user-facing workflows and engineering quality practices.