19 weighted checks, recomputed on every keystroke, with no model in the loop — so the same resume always scores the same. The AI coach asks you for the metric instead of inventing one. Then we render your real PDF and read it back.
92/100
17 of 19 checks
That pipeline migration — how many services, and what did runtime go from and to?
12 services, 6h down to 40m
Before you accept
Migrated the nightly pipeline serving 12 services, cutting runtime 6h → 40m.
19
weighted ATS checks, recomputed live as you type
±8
the most the AI can move your score — the rest is rules
0
metrics invented. If we need a number, we ask you for it
Most builders give you a number and no way to check it. Here you can see exactly where every point came from — and how much of it an AI was allowed to influence.
Layer 1
19 weighted checks totalling 100 points — contact fields, role depth, quantified bullets, action verbs, length. It is a pure function with no model in it, so the same resume always scores the same, and it recomputes on every keystroke.
Deterministic · runs locally · free
Layer 2
An LLM judges specificity, phrasing and ATS-friendliness, then gets blended 70/30 with the checklist and clamped to ±8 points. The model can inform your score. It cannot swing it.
Blended 70/30 · clamped ±8
Layer 3
We render your real PDF, extract the text back out, and diff it against your data — so you see which fields survived, which sections were found, and whether a two-column layout got read out of order.
Renders the real export
Ask most AI writers to strengthen “Led the data pipeline migration” and you get a team size, a latency figure and a cost saving — none of which came from you. It reads well until an interviewer asks about the number.
Ours can't do that. When a bullet is missing a metric, it asks you a short, specific question and uses your answer. If you don't have a figure, it improves the wording and tells you plainly that the gap is still open.
And every suggested edit shows what it earns before you accept it — because the checklist is deterministic, we can score the change without committing it.
Proposed
Migrated the nightly data pipeline serving 12 services, cutting runtime from 6 hours to 40 minutes.
Every number in that rewrite came from the answer above.
Two are single-column and parse cleanly. The third looks better and parses worse — and we tell you so in the app, every time you pick it.
Modern
Single column. Typical ATS software reads sections in the same order you see.
Classic
Single column serif. Typical ATS software reads sections in the same order you see.
Creative
Two columns. ATS parsers often read the sidebar (skills, education) before experience.
Give us a few facts and AI writes a full resume, or upload an existing PDF and we parse it into editable sections. Blank start is there too. Your first AI draft is free.
The checklist updates as you type. Work through the gaps it flags — the coach asks you for anything it can't know, and shows what each change earns before you accept it.
Run the parse report to see what an ATS extracts from your real PDF. Unlock for ₹69 and export.
The ATS checklist is free and unlimited. Pay only when you want the AI layer and the PDF. Lock in the launch price before it goes up to ₹199.
Free
No card. No time limit.
AI features
One-time, for one resume. Not a subscription — nothing renews.
Access expires 3 days after payment · your data is never deleted
No refunds once AI features are accessed. Refund policy
Your resume is yours. We don't sell your data, and we don't delete it when access expires.