Help & FAQ

An Applicant Tracking System (ATS) is software that helps companies manage hiring — posting jobs, collecting applications, screening resumes, moving candidates through pipeline stages, scheduling interviews, and keeping an audit trail of every decision. Traditional systems mostly track where candidates are in the process. HireSagar goes further: it evaluates candidates with AI, so you get a fit score, evidence, risk flags, and interview questions — not just a list. See how it works or try the live demo.

AI resume screening reads a resume the way an experienced recruiter would and compares it against a job's requirements. In HireSagar, a deterministic layer first extracts the facts — name, contact details, skills, employment dates, and gaps — in under 100ms. Deeper reasoning stages then run in parallel to assess skill depth, experience consistency, timeline coherence, job-description alignment, and career trajectory. Every score links back to a specific passage in the resume, so the result is auditable rather than a black box.

Resume parsing is the automated extraction of structured data — name, email, phone, location, skills, job titles, companies, and dates — from an unstructured PDF or Word document. HireSagar parses resumes deterministically before any AI runs, which keeps the facts accurate and lets the analysis continue even if an AI step is unavailable. You can watch it happen on a real file in the interactive demo, no signup required.

HireSagar never auto-rejects a candidate. It scores and ranks applicants and surfaces evidence and risk flags, but the hiring decision always stays with a human recruiter. This is deliberate: automated rejection is both a fairness risk and, in several jurisdictions, a compliance risk. Scores are decision support, not a gate.

Instead of keyword matching, HireSagar scores the semantic alignment between a job description and a candidate's actual experience — weighing skill depth (practical vs. merely listed), years of relevant experience cross-checked against real timeline dates, and seniority fit. That's why two candidates applying to the same role receive different, candidate-specific interview questions rather than a generic template.

Small teams need an ATS that is fast to set up, affordable, and doesn't require a dedicated recruiting operations person. HireSagar starts at a low monthly price with a 7-day free trial and no credit card, runs the full deterministic scoring engine on every plan, and works out of the box with sensible default pipelines. Compare plans on the pricing page or read our guide on choosing an ATS for a small team.

ATS pricing ranges widely — from free tiers to enterprise contracts running into thousands per month, often priced per recruiter seat or per job slot. HireSagar uses transparent monthly plans with a generous AI-credit allowance and a 7-day free trial; there are no setup fees and no per-candidate charges. Current prices are always live on the pricing page.

Yes. Each open job has a public careers page where candidates can submit their details and resume directly — no account, no password. Their application flows straight into your pipeline for screening. This removes friction that otherwise causes strong candidates to drop off before applying.

Yes. HireSagar is location-agnostic — it extracts and reasons about candidate locations, and the intelligence engine works across industries and countries. Interview scheduling handles the logistics regardless of where your team or candidates are based, so remote, hybrid, and cross-border hiring all work the same way.

HireSagar is a Hiring Intelligence Platform — an Applicant Tracking System (ATS) built on a deterministic, explainable scoring engine, with model-backed reasoning layered on top of it rather than underneath it. It helps you:

• Create jobs with a fully customizable hiring pipeline (Applied → Resume Screen → Coding Test → Written Assessment → Interviews → Offer, etc.)
• Automatically analyze resumes against a job's requirements — extracting name, contact info, skills, experience, and a fit score
• Schedule and track interviews and assessments, with conflict detection, due dates, overdue alerts, and rescheduling
• Evaluate written/coding assessments and interview transcripts with deterministic, evidence-based scoring — every score traces back to a phrase actually present in the submission or the interviewer's notes
• View analytics across your pipeline, and keep a full activity log / audit trail of everything that happens to a candidate

The Dashboard is your daily action list — what needs your attention right now. It shows headline numbers (open jobs, total candidates, interviews this week, pending assessments), a Needs Attention card listing every overdue interview and assessment so nothing slips through the cracks, the live Hiring Funnel across all jobs, your top jobs by applicant volume, upcoming interviews, and a feed of recent activity. Use it as your daily "what's outstanding and what changed" view.

For trends and performance over time, see Analytics instead — the Dashboard intentionally stays focused on today's open items rather than historical charts.

Go to Jobs → Create Job. Fill in the title, department, location, level, required skills, nice-to-have skills, and education requirements — these fields drive the AI resume scoring, so the more specific you are, the more accurate the candidate match scores will be. You'll also choose or customize the hiring pipeline for this job.

Yes — pipelines are per-job and fully configurable. A typical pipeline might be: Applied → Resume Screen → Coding Test → Written Assessment → Technical Interview → Final Interview → Offer → Hired, but you can add, remove, reorder, rename, recolor, and re-icon stages from Jobs → [Job] → Edit → Pipeline. The system automatically detects which stages are "assessment" stages (anything with "test", "assessment", "coding", or "written" in the name) and which are "interview" stages, so scheduling and overdue logic work correctly no matter how you name your stages. Editing a job's own stages is included on every plan, including Free. Saving a stage set as a reusable named template to apply to future jobs is a Business and Enterprise feature — but templates you already have stay readable on any plan, so downgrading never makes an existing pipeline unusable.

Open a candidate's profile and use the Move to Stage control to advance (or move back) a candidate. Every move is recorded in the candidate's stage history with who moved them, when, and any notes — this becomes your audit trail for that candidate's journey through the pipeline.

Note: in Jobs → [Job] → Candidates, the stage column is display-only (just a badge showing the current stage) — this is intentional, so stage changes always go through the candidate profile where the full history is recorded.

Active — open and accepting candidates. Interviewing — typically used once you have candidates in interview stages, useful for filtering. Closed — no longer hiring for this role, but kept for records. Archived — hidden from default views but fully retained, including all candidate history.

Yes, and neither loses anything. Open the job and use Reopen on a closed job or Unarchive on an archived one — candidates, stage history, notes, interviews and scores all come back exactly as they were, because closing and archiving only ever changed the job's visibility, never its data.

The distinction is worth knowing: closed freezes the workflow (no new applications, no AI spend on that role) while archived is read-only and hidden from your default lists. A job that closed automatically because it passed its expiry date is reopened the same way — extending the end date on a closed job does not by itself reopen it, so set the new date and reopen it.

When you upload a resume (PDF, DOCX, TXT, or Markdown), HireSagar extracts the candidate's name, email, phone, location, total experience, skills, education match, and key achievements, then compares them against the job's required and nice-to-have skills to compute a fit score and a recommendation (e.g. Strong Match, Possible Match, Weak Match). It also flags any skill gaps relative to the job requirements.

The parser is built to handle many resume formats and writing styles — plain prose, bulleted Markdown with headers, ALL-CAPS layouts, "Name: ..." labeled templates, and more — so scores stay reliable however a candidate's resume happens to be formatted.

The score blends required-skill coverage (weighted most heavily), nice-to-have skill coverage, experience level vs. the job's level, and education match. A high score means the resume's content closely lines up with what the job description asks for — it's a starting signal for prioritization, not a final hiring decision.

You can always edit a candidate's details directly from their profile. If you notice a resume format that consistently confuses the parser, that's valuable feedback — diverse formats (Markdown resumes, ALL-CAPS resumes, "Name:"-labeled templates, etc.) are specifically tested against to keep extraction accurate, but no parser is perfect for every layout.

That table now shows the candidate's current stage as a read-only badge. To change a candidate's stage, open their profile and use the dedicated Move to Stage action — this ensures every stage change is properly logged in the candidate's history and triggers any related scheduling logic (e.g. creating an assessment when moving into an assessment stage).

No — that's expected, and it's deliberately shown differently so it can't be mistaken for a live call to action. A recommendation badge (whether on the candidate list, an interview, or an assessment) reflects the AI's read of the resume/interview/assessment at the time it was analyzed — it's a historical record, not a current suggestion.

Once a candidate is rejected (or hired), any recommendation badge for them is shown muted/italic with a tooltip explaining it reflects that round only and the candidate's status has since changed. The decision to reject (or hire) always overrides whatever the recommendation said — the badge is just kept visible for audit/context, e.g. "this candidate scored well on paper but was rejected after the interview, here's why."

Yes — drop as many files as you like into Upload Resumes on any job and they are parsed and scored together.

The part worth knowing is what happens when one file in the batch is bad: the rest still go through. A single unreadable PDF has never been allowed to fail the whole upload. Each problem file is reported individually and told apart, because they need different fixes from you:

• Rejected — the file was refused before reading: too large, not a résumé format we accept, or it failed the malware scan. Re-export it and try again.
• Unreadable — the file was accepted but no text could be recovered from it, even after OCR. Usually a corrupted PDF or a photo too low-resolution to read. Nothing is stored for these, so they cost you no storage.

Duplicate candidates are detected by email address against the same job, so re-uploading a batch does not create a second copy of anyone.

From a candidate's profile (or the Interviews section), choose Schedule Interview, pick the round/type, date, time, duration, and interviewer. The system checks for double-booking — if the candidate or interviewer already has another session too close in time (within the minimum gap), it blocks the save and tells you exactly which existing session conflicts and at what time, so you can pick a different slot.

The interview is automatically flagged as Overdue — you'll see an "Overdue" badge on the interview, on the candidate's record, and in the Interviews list/stat cards. This makes it easy to spot interviews that were scheduled but never followed up on (no feedback entered, no status change), so nothing falls through the cracks.

Open the interview, mark it Completed, and enter your feedback (and optionally a transcript). The system requires at least a sentence or two of real feedback — it won't let you submit an empty completion. From that feedback (and transcript, if provided), it computes communication, technical, and confidence scores, a recommendation (e.g. Strong Hire / Hire / No Hire), and a written reasoning summary highlighting strengths and concerns — all grounded in what you actually wrote, never invented from nothing.

Go to Assessments → Create Assessment (or trigger it from a candidate moving into an assessment-type stage like "Coding Test" or "Written Assessment"). Choose the candidate, the pipeline stage/round, and assessment type (coding or written). The system can auto-suggest relevant questions based on the candidate's experience level and the job's required/practical skills.

Yes — when creating (or later editing) an assessment, set an optional Due Date and Due Time. The deadline appears on the assessment's detail page as a "Due" stat, and on the Assessments list alongside each pending/submitted item, so candidates and reviewers always know the timeline.

It's automatically marked Overdue with a visible badge — on the assessment itself, in the Assessments list, and in the relevant stat counts. This applies only while the assessment is still pending (an evaluated/submitted assessment is never shown as overdue), so you can quickly see which candidates missed their deadline and decide whether to follow up or reschedule.

Yes. From the assessment's detail page, click Reschedule Due Date (or Set Due Date if none was set yet), pick a new date/time, and save. The change — including the previous deadline — is written to the activity log, so there's a clear record of why and when a deadline moved.

Yes — an assessment can only be marked as submitted if it actually contains a non-empty answer. Empty submissions are rejected rather than silently being recorded as "submitted", so the Current Assessments view always reflects genuinely completed work.

Both Interviews and Assessments list pages have a dedicated "Overdue" stat card showing the count, and every overdue item is badged inline wherever it appears — in lists, on its detail page, and in candidate views. "Overdue" simply means: the scheduled date/time (or due date/time) has passed, and the item is still in a pending/scheduled state with no outcome recorded yet.

Both follow the same pattern: a Reschedule button appears on items that are still pending/scheduled (not on completed/cancelled/evaluated ones). Reschedule opens a small dialog with date/time inputs pre-filled with the current schedule and a minimum date of today. Saving:

1. Re-runs any relevant conflict checks (for interviews — the same double-booking guard as scheduling)
2. Updates the record's date/time
3. Clears the "Overdue" state if the new time is in the future
4. Writes an activity log entry recording the old and new times, so there's always a paper trail

Where the Dashboard answers "what needs my attention today", Analytics answers "how is hiring performing over time" — they're deliberately built to show different things, not the same numbers twice. Analytics has:

• Conversion by Job — of everyone who applied to each role, what share is currently hired (a performance read on that pipeline)
• Monthly Trends — applications vs. hires over the last 6 months
• Top Jobs by Applications — your highest-volume roles
• Score Calibration — whether the AI resume-scoring rubric actually predicts who advances, with a link to the full per-job breakdown on Platform Intelligence

Use Analytics for reviews and reporting; use the Dashboard for day-to-day triage.

Platform Intelligence (in the sidebar) is where HireSagar shows its own adaptive layer: every skill-evidence correction it has learned, and whether its resume-scoring rubric actually predicts real pipeline outcomes for each job. It's entirely read-only — nothing on this page changes how any individual candidate was or will be scored. Think of it as "how the platform is getting smarter, and proof that it is."

It learns automatically by default. Every time an interview is marked Completed and analyzed, HireSagar scans the interviewer's own feedback (and transcript, if provided) for evidence of any skill the candidate's resume had marked "missing" — if the interviewer mentions it, that skill gap is automatically upgraded and the candidate's score/recommendation is recomputed on the spot. This is recorded as a correction from "System (interview feedback)" on the Platform Intelligence page.

Recruiters can additionally record evidence manually from a candidate's "Skills" tab using "Found evidence on resume?" — useful if you spot something outside of an interview (e.g. in a portfolio or reference call). Both paths feed the same learning system: once the same (skill, phrase) combination has been confirmed twice — automatically or manually, in any combination — it becomes a permanently "Active" alias applied to every future resume that requires that skill, for any job.

Score Calibration groups every recorded pipeline outcome (advanced / rejected / hired) by the candidate's resume score band at the time, per job — so you can see, e.g., "candidates scoring 75-87 for this role advance 80% of the time, but candidates scoring 65-74 almost never do." It's purely descriptive context for recruiters deciding whether a job's score thresholds feel right.

It never changes any candidate's score automatically — by design, every candidate is scored the same explicit way at analysis time, so scoring stays fair and auditable. The Analytics page shows a condensed "overall advance rate" headline version of this same data; Platform Intelligence has the full per-job, per-band breakdown.

Sagar is HireSagar's hiring intelligence engine in conversational form — it has live access to your organization's jobs, candidates, interviews, and assessments, and answers with evidence from your own records. You can ask it things like:

• "Who are my top candidates right now?"
• "Which candidates have high risk flags?"
• "Compare my top 3 candidates for the Senior Engineer role"
• "Which job has the most pending candidates?"
• "Summarize the hiring pipeline"

It draws only from your organization's data — it will never fabricate information or reference data from other organizations.

Sagar is available to all team members with at least Member access. Viewers (read-only) cannot access it, since it surfaces full candidate scores, risk signals, and pipeline state.

Team lists everyone with access to your HireSagar workspace, their roles, and which jobs/activity they're associated with — useful for understanding who's responsible for moving a candidate forward.

Settings covers your profile (name, contact info, password), organization details, notification preferences, and theme & appearance (light/dark mode — also toggleable from the moon/sun icon in the top bar).

It is also where the account-level controls live: two-factor authentication, active sessions, your public careers page, screening questions, email templates, pipeline templates (creating reusable ones needs Business or Enterprise; a job's own stages are editable on every plan), data export, and the integration settings (job boards, webhooks, API keys and SSO) where your plan includes them.

Settings → Two-Factor Authentication. Scan the QR code with any authenticator app — Google Authenticator, Authy, 1Password, Microsoft Authenticator — and confirm one code to enable it. This is standard TOTP, so it works offline and does not depend on SMS.

You are given backup codes when you enable it. Save them somewhere that is not your phone: if you lose the device, they are how you get back in. Each one works once, and you can regenerate the set at any time (which invalidates the old ones).

Separately, Active Sessions shows every device currently signed in to your account and lets you sign any of them out remotely — the first thing to do if a laptop goes missing.

A traditional Applicant Tracking System tracks candidates: it records who applied and what stage they're in. A Hiring Intelligence Platform evaluates them. HireSagar reads every resume, grades the evidence behind each required skill, sums real employment tenure month by month, detects timeline gaps and overlaps, scores fit against the specific role, and flags what to probe in the interview — then shows you the passage every conclusion came from. You get a defensible shortlist with reasoning attached, not a queue to work through manually.

Deterministically, from three weighted measures: skills match (40%), experience match (40%) and education match (20%).

• Skills — every required and nice-to-have skill is graded demonstrated (named alongside real work), listed only, related evidence found, or missing. Required skills carry 70% of the skills figure, nice-to-haves 30%.
• Experience — employment months are summed role by role with overlapping roles merged, so a gap between jobs is never counted as tenure. The total is compared against the role's seniority band.
• Education — the highest degree found is compared with the role's stated requirement.

A hard floor also applies: if a role lists 3+ required skills and a candidate matches under 20% of them, the score is capped — years on paper can't paper over a domain mismatch.

Fully explainable, by design. The foundation of HireSagar is a deterministic engine — rules and pattern matching over the resume's own text — not a language model's opinion. The same resume against the same job always produces the same score, and every element traces back to something concrete: a date range, a skill mention, a matched requirement. Advanced AI reasoning is layered on top of those facts as an enhancement, never as the foundation, and if it is unavailable the deterministic analysis still stands on its own. You can also correct any skill grade yourself, and the score recomputes with the identical formula.

Yes. Our free hiring intelligence tools run the same deterministic engine with no account required — check a resume's ATS compatibility, extract its skills, analyse its career timeline, or score a resume against a job description. You can also explore a full recruiter workspace on sample data in the live demo.

Yes — by email forwarding, which is how those boards actually notify you. Included on Business and Enterprise.

In Settings → Job board applications you generate a unique forwarding address. Add a rule in your mail client (or your careers inbox) that forwards board notifications to it, and each application is parsed, scored and filed automatically — the résumé goes through the same deterministic pipeline as a résumé a recruiter drags in, so a candidate from LinkedIn is scored identically to one uploaded by hand.

You can point an address at one specific job, or use a catch-all address that matches the job title in the subject line. If a catch-all message can't be matched to an open job, it is reported rather than guessed — filing someone against the wrong role is worse than not filing them, and the reason appears on the settings page so you can fix the rule.

That page also counts everything received, created, duplicated and rejected, with the last error shown in plain language. This matters more than it sounds: without it, "my forwarding rule was never set up" and "forwarding works and every message is being rejected" look identical from the outside.

Because it works with every board, including the ones that have no public API and the internal job boards and agency feeds that will never have one. A per-board integration only covers the boards someone has built a connector for, and breaks whenever a board changes its API or its terms.

Forwarding is also honest about what it is: you can see exactly which messages are being forwarded, turn a single address off without touching anything else, and revoke it entirely at any time. HireSagar never needs your job-board password, and never signs in as you.

Yes. Included on Business and Enterprise. Configure endpoints in Settings → Webhooks and receive a signed POST for: candidate.created, candidate.stage_changed, candidate.hired, candidate.rejected, job.created, job.closed, interview.scheduled and interview.completed.

Deliveries that fail are retried automatically with backoff, so a few minutes of downtime on your endpoint does not lose the event, and every attempt is recorded so you can see what was sent and what came back.

Yes — a REST API at /api/v1, authenticated with a key you create in Settings → API Keys. Included on Professional, Business and Enterprise.

It covers jobs, candidates, interviews and your current usage. Be aware that it is deliberately read-only today: it is for reporting, dashboards and syncing data into your own systems, not for creating or modifying records. We would rather say that plainly than let you discover it halfway through building against it. Full endpoint documentation is linked from the same settings page.

Keys carry the permissions of the plan that issued them and can be revoked individually at any time.

Your trial gives you full access to HireSagar for 7 days. When it expires, your account switches to a read-only state — you can view existing jobs and candidates, but cannot upload new resumes or use AI features until you upgrade. Your data is preserved.

Go to Settings → Plan & Billing and click the plan you want, or visit the Pricing page. You'll see "Upgrade to [Plan]" buttons if you're logged in. Plan changes take effect immediately.

Your Intelligence Operations allowance resets on the 1st of each month. The reset happens lazily — on your next Hiring Intelligence request or resume upload after the 1st, the system checks whether the reset date has passed and resets usage automatically. No manual action is needed.

The bell icon in the top bar shows in-app notifications for:

• Candidate moved — a candidate advanced through a pipeline stage
• Interview scheduled — an interview was booked for a candidate
• Interview completed — an interview was marked complete with feedback
• Assessment submitted — a candidate submitted a take-home or coding assessment
• Invite accepted — a team member accepted their invite and joined the org
• Analysis complete — resume upload + analysis finished
• Usage warning — your Intelligence Operations crossed 80% usage for the month
• Trial expiring — your trial is expiring within 3 days

Stage change, interview, and invite notifications go to all Owners and Admins. Analysis-complete notifications go to the person who triggered the upload. Credit warning notifications go to the organization owner only.

No — submissions are validated before being accepted, so a submission with no actual answer content cannot be marked as "Submitted". If you see an assessment still showing "Pending", the candidate (or reviewer) needs to enter their answer first.

Make sure the outcome was actually saved: for interviews, mark the status as Completed (with feedback) or Cancelled; for assessments, mark as Submitted and then evaluate it. The Overdue badge only clears once the item is no longer pending, or once its date/time is rescheduled into the future.

This means either the candidate or the interviewer already has another session within the minimum required gap on that day. The error message names the conflicting round and its time — pick a slot that leaves enough room before/after that session, or reassign the interviewer.