RESAT
The professional's edge in automated recruitment.
Resat addresses the 'hidden barrier' of recruitment—Applicant Tracking Systems (ATS). It combines structured data input, multi-model AI optimization (GPT-4, Claude, Gemini), and server-side LaTeX compilation to produce high-impact resumes that bridge the gap between automated filters and human eyes.
Combines real-time ATS scoring, AI-powered keyword extraction, and LaTeX-based professional PDF generation in one high-performance platform.
The Challenge
Most resume builders prioritize visual aesthetics over technical parseability. Non-standard layouts and missing keywords cause ATS systems to misparse or reject qualified candidates, while traditional editors lack real-time scoring against actual job descriptions.
The Solution
A dual-approach system: content quality and format quality. Resat uses a dedicated LaTeX microservice for print-perfect, parseable PDFs and a real-time Score Analyzer that evaluates resumes against job descriptions, providing actionable feedback on keyword match, impact, and completeness.
LaTeX-Powered Résumé Engine
Moves beyond HTML/Word templates by using server-side LaTeX compilation via Docker. Produces typographically clean, ATS-optimized documents from structured form data or raw text input.
Real-Time ATS Score Analyzer
Evaluates resumes against specific job descriptions using server-side PDF parsing. Scores metrics on parsing quality, keyword alignment, and impact, providing section-by-section improvement guidance.
Multi-Model AI Content Rewriter
Integrates OpenAI, Gemini, and Anthropic via a configurable strategy. Rewrites content for maximum impact, aligns technical keywords, and assists in direct LaTeX code editing and fixing.
Template & Version Management
Enables rapid iteration by saving multiple resume variants and custom LaTeX templates with live thumbnails. Powered by persistent LocalStorage for privacy and zero-latency access.
Structured vs. Raw Text Logic
Flexible input modes allowing users to either fill structured forms or paste existing content, both of which are automatically escaped and mapped to Mustache-style LaTeX templates.
Recruiter-Persona Feedback
AI-powered insights that simulate recruiter perspectives, identifying strengths and weaknesses in the narrative while adjusting scores based on the specific context of the target role.