01
Candidate strength
A calibrated profile score built from experience depth, proven skills, resume craft, GitHub evidence, and professional completeness, with the single largest gap named, not a vanity percentage.
Job-search intelligence
US · India · UK/EU
Spend your efforton roles thatactually fit.
Atlas reads your profile, your proof of work, and live postings as one system, so you can see where you actually fit, what is holding the score back, and what to do about it before you spend another evening applying.
Match signal
82
Strong fit
Backend Engineer
Nexa Labs, Bengaluru
- Skill coverage
- 88
- Seniority fit
- 74
- Company score
- 80
- Posting freshness
- 91
Missing: Kafka. Everything else is covered by shipped work.
Illustrative. Every score opens to its drivers.
(01) The system
Inputs, signals, decisions
Everything you already have, read as one signal.
Nothing you have to maintain by hand.
Jobsearchfailsonfragmentation,noteffort.Atlastakesthesourcesyoualreadytouch,turnseachintostructured,versionedfeatures,andletseverydownstreamnumberpointbacktotheexactinputthatproducedit.
Inputs
ResumeParsed into sections, dates, claims
GitHubRepos, languages, shipped work
LinkedInHistory and role progression
Job boardsATS boards, startups, internships
Company dataHiring velocity, pay, stability
Your inboxReplies detected in-browser, headers only
Signal layer
Live
Atlas signal layer
Versioned features, one contract
Outputs
Match scoreDecomposed into ten drivers
Candidate strengthCalibrated, not a vanity number
Compensation fitBands compared to your floor
Resume fixesRanked by what moves the score
Application timelineOne thread per role
Outcome learningEvery result feeds ranking
Six inputs, one signal layer, and every number traceable to the row that produced it
01
Job search is still run out of a spreadsheet.
02
And everyone has quietly accepted that.
03
Twenty tabs, three trackers, and no idea which application is worth the next hour.
04
So we connected them.
(02) Intelligence layer
Signals into scores
Scores that explain themselves.
Because a number you cannot argue with is useless.
Atlasseparatessignalextractionfromscoring.Profiles,jobs,companies,applications,andoutcomesbecomeversionedfeaturesfirst;recommendationsarebuiltfromthosefeatureslater,sonothingisablackbox,andnothingsilentlychangesunderneathyou.
02
Company intelligence
Company quality from five measured signals: responsiveness, hiring velocity, posting freshness, time to first response, and whether the employer is verified. Each carries its sample size, so a score from four applications is not shown as settled.
03
Explainable matching
Every match opens to its ten drivers: skill coverage, missing must-haves, seniority fit, domain alignment, compensation fit, location and remote fit, employer signal, your strength against the role bar, posting freshness, and competition. Open any score and you see the arithmetic.
04
Canonical skills
Skills resolve to canonical entries, not raw strings, so "Postgres", "PostgreSQL", and "psql" count once. Coverage is measured against what the role requires, weighted by what it insists on.
05
Deterministic ATS
Parseability, structure, and content checks run as fixed rules. Same resume, same score, every time. Language suggestions stay advisory and never move the number.
06
Freshness that decays
A 40-day-old post is not the same opportunity as one from this morning. Freshness decays continuously and reposts are collapsed, so a stale listing cannot masquerade as a live one.
07
Assisted, not automated
One-click apply on Greenhouse, Lever, and Ashby. Everywhere else the browser extension fills the form in your own session, highlights what it could not map, and you click Submit. Atlas never submits silently.
08
Data that learns
Feature snapshots and outcome logs let ranking improve over time, with replies, interviews, offers, and rejections all feeding back, without changing how the product feels to use day to day.
(03) Inside the product
One workspace
See the work, not just the pitch.
Four surfaces from one account, populated.
Thesamescreensyouuseeveryday:amatchreadoutthatopenstoitsdrivers,aresumeworkspacethattellsyouwhattofixfirst,onetimelineforeveryapplication,andtheconnectorsthatturnclaimsintoevidence.
app.myjobatlas.site/match/nexa-labs-backend
Ananya Raghavan
Backend engineer, 3 yrs, Bengaluru
82
Strong fit
Backend Engineer
Nexa Labs, Bengaluru
- Skill coverage
- 88
- Seniority fit
- 74
- Company score
- 80
- Posting freshness
- 91
Skill coverage
PythonFastAPIPostgreSQLKubernetesGoRedisKafka, missing
Illustrative. Every score opens to its drivers.
Explainable match signal
One score, ten drivers, and the arithmetic behind them. Open a match and you can see which factor is carrying it and which one is holding it back, before you spend an evening on the application.
What you are looking at
- Drivers are weighted and the weights are visible
- Missing required skills are named individually
- The role bar is compared to your track record, not your title
- Score history keeps the number honest as the post ages
Weighting
Expert, versioned
Recompute
On profile change
Fit
Ten drivers — coverage, gaps, seniority, domain, pay, location, employer signal, role bar, freshness, competition — scored together, not guessed.
Proof
Resume claims are checked against projects, GitHub evidence, profile data, and parsed work history.
Loop
Applications and outcomes are logged, so ranking keeps learning which signals actually matter.
(04) Workflow
Collect, score, act, learn
Built around the full search loop.
Mosttoolsownonestepandhandyoutherest.Atlascollectsthemarket,turnsitintoscoresyoucanarguewith,strengthenstheprofileyousendout,thenrecordswhatactuallyhappenedsothenextrankingissharperthanthelast.
01
Collect the right market
Atlas keeps one shared index of roles and companies across official ATS boards, aggregators, startup listings, and URLs you drop in. Each post is parsed into skills, seniority, location, pay, source, and freshness, so you start from structure instead of a hundred open tabs.
- One shared index
- Duplicate posts collapsed
- Dead listings quarantined
02
Score fit honestly
Fit is more than resume-to-job keyword overlap. Atlas weighs proven skills, seniority match, company quality, location, compensation, posting freshness, and your own profile strength into one match score you can actually defend.
- Ten weighted drivers
- Weights are visible
- No single opaque percent
03
Strengthen your profile
Resume parsing, ATS checks, completeness scoring, GitHub evidence, and LinkedIn imports show exactly what is strong, what is missing, and what to fix next for the role you are actually chasing.
- Deterministic ATS checks
- Claims matched to evidence
- Fixes ranked by impact
04
Move applications forward
Applications, cold emails, portal submissions, replies detected by the browser extension, interviews, assessments, and follow-ups live on one timeline, not scattered across spreadsheets, inboxes, and memory.
- Replies detected in your browser
- Follow-ups surfaced
- One thread per role
05
Use contacts with context
Referral posts, contacts, company notes, and recruiter threads stay tied to the roles and companies they can actually influence, so a warm intro never gets lost.
- Contacts tied to roles
- Outreach history kept
- No CRM busywork
(05) Connectors
Opt-in, revocable
Claims are cheap.
Evidence is what moves a score.
Anyonecanlistaskill.Atlaswouldratherseethecommit.Connectthesourcesyoualreadyuseandyourprofilestopsbeingself-reported.
Proof of work
GitHub
Repositories, languages, commit recency, and project scope become skill evidence. A claimed skill with shipped code behind it is weighted differently from one without.
read:user, user:email
Reply detection
Browser extension
Reads sender, subject, and date from the mail already open in your browser and moves the matching role forward on your timeline. The message body never leaves the page, and Atlas holds no mail scope.
Headers only, in-browser
History import
Roles, dates, and progression import once, so seniority fit is measured against an actual track record rather than a job title.
Profile and history
Every connector is optional. Atlas works without any of them. It just has less to go on.
(06) Who it is for
Built for people who need a repeatable system.
Atlas works best when the search has many moving parts: roles, documents, people, deadlines, and follow-ups. It keeps them connected instead of scattered.
Students & fresh graduates
Find internships and first roles, build real resume evidence, track cold emails, and learn which profile gaps matter most right now.
Professionals changing roles
Prioritise realistic opportunities, compare companies, tailor resumes, and keep interviews, assessments, and follow-ups in one place.
Referral-led searches
Connect people, companies, role context, and outreach history, without turning your job search into a sales pipeline.
(07) Getting started
Free while in early access
What the first week looks like.
No sales call, no onboarding project.
Day 1
01Profile in, first scores out
Add a resume and your target roles. Atlas parses the file, runs the ATS checks, and returns your candidate strength and a first shortlist.
Day 2 to 7
02Evidence and shortlist
Connect GitHub or install the extension if you want richer signals. The shortlist tightens as skills resolve to canonical entries and stale postings drop out.
Week 2+
03The loop closes
Applications, replies, and interviews land on the timeline. Outcomes start feeding ranking, so what surfaces next is shaped by what actually worked.
What it costs you
- Free while Atlas is in early access
- No card, no trial clock
- Export or delete your data at any time
- Connectors are optional and revocable