Run Your Job Search Like an Operating System.

It reads you first

Drop in a resume PDF, paste a LinkedIn export, or type a free-form note. Atlas extracts your headline, role history, skill set, education, and career patterns into a structured profile you can edit field-by-field. The skills review tool flags reordered duplicates like 'ERP / CRM / MRP Implementation' versus 'CRM / MRP / ERP implementation' before they distort downstream scoring. Field caps are generous: 10,000 characters of summary, 200 experience entries, 200 achievements, so you don't have to compress the truth of what you've done.

Resume parsing, LinkedIn enrichment, and a 10,000-character free-form context bucket the AI references for nuance.

It searches for you nightly

Every morning at 04:30 ET, Atlas hits LinkedIn, Indeed, Glassdoor, Google Jobs, and ZipRecruiter and pulls roughly 600 listings. A deduplication pass merges cross-board duplicates. Each remaining role gets a 0–100 fit score computed against your profile and the scoring rules Atlas has learned from your feedback. The ranked shortlist is waiting on your dashboard before your first coffee: no tab avalanche, no scrolling five job boards yourself.

5 boards aggregated · ~600 listings deduplicated · 0–100 fit score per role · 04:30 ET daily.

It sharpens every time you click

Mark a role 'interested' or 'dismissed' and tell Atlas why in one sentence. After five signals the model synthesizes persistent scoring rules: negative weights for patterns you reject, positive weights for the ones you chase. Rules Studio at /app/rules exposes every learned rule directly. You can edit, delete, or add rules by hand. The dashboard keeps the raw signal next to the synthesized rule so you can inspect each change before it affects tomorrow's rankings. Everything is editable. Nothing is locked in a black box.

Feedback compounds. After ~5 signals the LLM writes persistent rules you can read and edit.

Profile editor with intent

Edit every field of your AI-generated profile. Headline, summary, skills, experience, education, achievements, career patterns, and an additional-context bucket. Field caps are wide on purpose: 10,000 characters of summary, 10,000 characters of free-form context, 200 experience entries, so you write what's true, not what fits. Validation errors come back as human-readable toasts instead of JSON.

Skills review catches what eyes miss

Open the Review Skills modal and Atlas surfaces fuzzy duplicates across three matching layers: case-insensitive compaction (Node.js to nodejs), token-set Jaccard for reordered phrases (CRM/MRP/ERP versus ERP/CRM/MRP), and a tight prefix-augmentation check for variants like react versus reactjs. Single-word false positives stay out. You approve or skip each merge; nothing changes silently.

Career analysis that survives re-imports

Atlas writes a 10,000-character career pattern narrative from your resume and history. Edit it freely; your edits are flagged with a timestamp. If you re-upload a fresh resume, Atlas does not overwrite your edits. Instead it surfaces a banner showing the new import date alongside your last-edited date so you can decide whether to merge new signal in.

Rules Studio you can inspect

Atlas synthesizes persistent scoring rules from your feedback and writes them in plain English. Rules Studio shows every active rule in one place, with controls to edit, delete, disable, or add rules by hand. The editor sits beside role-score evidence, so changes are easy to verify before they shape the next run.

Multi-board nightly sweep

LinkedIn, Indeed, Glassdoor, Google Jobs, and ZipRecruiter, hit nightly. Roughly 600 listings deduplicated against each other and against the prior week's pulls. Each role is scored 0–100 with a per-role breakdown: what matched, what didn't, what disqualified. The ranked queue is waiting before sunrise so you start with decisions instead of sourcing.

Modular model harness

Atlas isolates LLM calls behind a typed model harness. Optional routing lets you swap models per task: a faster, cheaper model for parsing, a stronger model for scoring synthesis. No vendor lock. No prompts hidden in untouchable places. That keeps cost control, future tiering, and model downgrades in one place.

Who is Atlas for?

Atlas is for everyone. Atlas is built first for working people who've been pushed out by AI — because if there's a job you used to do well and now an algorithm does it cheaper, you shouldn't have to also do the painful search work alone. Atlas runs the disciplined sweep of the boards every night and surfaces what's actually worth your time. So you can focus on what your next stepping stone looks like.

How does Atlas work in plain English?

You upload a resume. Atlas parses it into a structured profile and a set of scoring rules. Every night at 04:30 ET, an agent scans five major boards, dedupes the results, and scores each role 0–100 against your profile. You wake up to a ranked shortlist instead of a hundred open tabs.

How much does Atlas cost during the beta?

Nothing. Beta access is free while we tune scoring with real users. Beta participants keep founding pricing for life once Atlas opens to the public.

What job boards does Atlas scan?

LinkedIn, Indeed, Glassdoor, Google Jobs, and ZipRecruiter. Every night. Roughly 600 raw listings dedupe into a ranked shortlist scored 0–100 against your profile and learned scoring rules.

How are matches scored?

Every role gets a 0–100 score with a per-axis breakdown: fit, seniority, scope, industry, compensation, and location. Each axis is graded against your structured profile and scoring rules, then weighted into the overall number. Open any match to see the breakdown and the model's reasoning per axis.

Does Atlas work if I'm not actively searching?

Yes. The nightly run keeps a passive search warm with zero effort. You'll only see roles that clear your scoring threshold, so the dashboard stays signal-rich. Most passive users check Atlas once a week and reach out only when something genuinely clears the bar.

Where does my data live?

Your profile, scoring rules, saved jobs, and feedback live in a private Postgres database tied to your account. Atlas is built on standard cloud infrastructure (Vercel for compute, Supabase for storage) and your row-level data is isolated from other accounts.

Can I edit what the AI wrote about me?

Yes. Every AI-generated field is human-editable: career analysis, summary, skills list, and scoring rules. Your edits persist across resume re-imports. The career analysis tracks an edited-on timestamp so you always know what's hand-written versus AI-written.