What is DeepResume?
DeepResume (haojianli.me) is an AI-powered resume optimization tool designed for new graduates and professionals with 1–5 years of experience. It has a single purpose: transforming "what you did" into "what impact you delivered."
Unlike most resume template tools on the market, DeepResume doesn't fabricate experience or stuff in keywords. Through structured diagnosis + Q&A-driven evidence enrichment + job description-aligned rewriting, it transforms every experience into something that resonates with interviewers and gets recognized by ATS systems.
Step 1: Upload Your Resume to Establish a Baseline Score
Supported formats: PDF, DOCX, or paste as text
After uploading, the system automatically parses your resume structure—identifying sections like work experience, education, project experience, and skills—and generates a baseline diagnostic report including:
- Overall Score (0–100): A composite evaluation of readability, quantified achievements, keyword coverage, and ATS compatibility
- Dimension Scores: Each dimension scored individually to pinpoint your weakest areas
- Actionable Checklist: Each issue comes with "why it's weak, where to fix it, how to fix it"
ATS Compatibility is an often-overlooked dimension. Many job seekers invest heavily in visual design without realizing that two-column layouts, embedded icons, and tables can prevent ATS systems from parsing their content correctly. DeepResume highlights which structures carry parsing risk.
Step 2: Paste a Target Job Description to Align with Role Requirements
If you have a job posting you're targeting, paste it in and the system will:
- Parse JD core requirements: Extract keywords, competencies, and hidden bonus criteria
- Generate a matching gap list: Compare against your current resume to flag missing keywords and weak spots
- Provide role-customized diagnosis: Engineering roles check for technical depth and performance evidence; PM roles check for goal decomposition and metric closure; business roles check for growth methodology and replicable strategies
No target JD? You'll still receive a general diagnosis and basic optimization.
Step 3: Q&A-Driven Rewriting — Not a Black-Box Rewrite
This is the biggest difference between DeepResume and other AI rewriting tools.
Most tools pass your resume directly into a large language model for rewriting—the output may look polished but is often inaccurate: technical details get generalized, metrics get fabricated, and the result drifts from your actual voice. DeepResume uses a Q&A-driven approach instead:
- Targeted questions surface based on weaknesses found in the diagnosis (e.g., "What was the user scale for this project?" "By how much did the metric improve after optimization?")
- You only need to fill in factual fragments from your actual experience—no need to rewrite everything from scratch
- Based on your inputs, three rewrite variants are generated: conservative, balanced, and enhanced
Each rewrite suggestion comes with a clear rationale. You can accept or skip item by item while preserving your own writing style.
Step 4: Review Diffs and Export to Apply
After accepting rewrite suggestions:
- Review the diff: Side-by-side comparison of before and after to verify each change matches your intent
- Check score changes: See which dimensions improved after the rewrite
- One-click export as PDF or DOCX: Clean format, ATS-compatible, ready to submit
Export formats support multiple languages including Chinese, English, Japanese, and Korean for international applications.
Typical Use Cases
New Graduates
Project experience from coursework or research tends to become a list of tasks: "participated in development of X project." DeepResume guides you to fill in goals, actions, collaborations, and outcomes—transforming academic, competition, and internship experience into more professional-sounding descriptions.
Before: Responsible for building the data visualization page, completing various charts and interactions.
After: Built a data visualization module for a course project (ECharts + React), including 6 general-purpose chart components and interaction conventions, improving component reuse across pages and reducing maintenance overhead.
Early-Career Professionals Changing Jobs
Work descriptions tend to stay at the adjective level: "optimized performance," "improved user experience." DeepResume helps ground these claims in metrics and evidence chains.
Before: Optimized page performance and improved user experience.
After: Addressed slow initial load times by reworking resource splitting and caching strategy, reducing first render time from 3.2s to 2.1s and decreasing critical path requests by 18%.
Privacy and Data
- Rewrites are scoped to facts you actually provide—no fabricated content
- We recommend starting with minimal information (sensitive details like phone numbers and addresses can be omitted)
- See our Privacy Policy and Terms of Service for details
Get Started Now
Upload your resume and receive your diagnostic report in under 3 minutes.