Tailor your resume
to every JD.

Paste a JD and we generate a tailored variant of your resume, same facts, JD-aligned terminology, reordered to put the most relevant work first. We never add skills you didn't list. Every variant is its own saved resume so you can score it, share it, or tailor it again against a different JD. One AI credit per variant.

No. Anti-fabrication is the hard rule that overrides everything. The AI may only reorder, rephrase, and tighten, it can never introduce tools, metrics, employers, or dates that aren't in your source resume. If the JD demands a skill you don't have, that gap is surfaced honestly in the score, not papered over in the rewrite.

On every JD you paste, our AI extracts which skills the recruiter treats as non-negotiable ("required", "must have", "minimum") vs. bonuses ("nice to have", "plus", "preferred"). Missing a must-have is a real blocker; missing a nice-to-have rarely costs you the interview. Knowing the difference tells you where to focus first.

An ATS is the software companies use to parse, store, and search every application; most mid-to-large employers run one. Contrary to the popular myth, recruiter surveys show an ATS rarely auto-rejects anyone. The real risk is quieter: a resume that parses badly or misses the keywords recruiters search for never surfaces to a human.

Yes. ATS scoring, keyword analysis, drive eligibility checks, and the application tracker are free forever, no credit card, no trial timer. AI-powered features (bullet rewrites, cover letters, suggestions) consume a small credit pool that we top up via share-to-earn and admin grants.

Twenty-seven deterministic local rules check machine readability, recruiter findability, and human-skim quality: section presence, action verbs, quantified achievements, date consistency, contact placement, and more. Each rule has a fixed weight and maps to published evidence, not ATS folklore, so two identical resumes always get the exact same score.

Most modern ATS engines (Workday, Greenhouse, Lever, Taleo) parse text-selectable PDFs cleanly. The risky cases are PDFs created via 'Print to PDF' (no text layer), scanned/image PDFs, multi-column layouts, and resumes with tables or text boxes. OptiResume flags these issues automatically.

Single-column. Research across eight major ATS engines shows single-column resumes parse correctly ~93% of the time vs. ~86% for multi-column, and the Skills section parse rate drops from 65% to 46% on two-column layouts. A two-column layout won't get you auto-rejected, that's a myth, but a Skills section that parses wrong is invisible to recruiter keyword searches.

One page. Recruiters at high-volume drives (TCS NQT, Infosys, Wipro Elite) spend roughly seven seconds on each resume, so anything spilling onto page two is unread. Keep it one page until you have three-plus years of real experience.

No. We parse your PDF/DOCX in memory, extract the text, and discard the original file bytes immediately. Only the extracted text, a SHA-256 hash for deduplication, and the analysis results are stored, never the raw PDF or DOCX.

Personally identifiable information (email, phone, addresses) is redacted from the prompt before it reaches the AI provider. All AI calls go through a single gateway that enforces redaction, caches responses to avoid duplicate exposure, and logs every call for audit.

A free pre-screening tool for the major Indian campus and off-campus drives, TCS NQT, Infosys, Wipro Elite, Accenture, Cognizant, and more. Enter your 10th, 12th, CGPA, backlogs, and gap months, and we tell you drive-by-drive whether you clear the cutoff before you spend hours applying. Targeting India campus placements? No other resume tool goes deeper.

The three most common reasons are: (1) ATS parsing fails on a multi-column or table-heavy layout, (2) the resume lists 'Responsibilities' instead of quantified achievements, and (3) the keywords from the job description aren't present in your resume. OptiResume diagnoses all three in under a second.

Yes, career-stage-aware feedback is a first-class feature. Freshers are scored on academic projects, certifications, coursework, and clubs/leadership instead of being penalized for missing 'three years of experience.' The Branch-Switcher mode also helps non-CS engineers reframe their background for tech roles.

Yes, and deeper than any other tool: the keyword diff loads Naukri and Internshala job descriptions natively, the eligibility checker tracks Indian recruiter cutoffs, college-tier context shapes the AI suggestions, and the cover-letter generator respects Indian phrasing conventions. The scoring itself is universal: parseable structure, quantified bullets, and JD keyword match work the same in any market.