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Products · ATS by pPulse

Hire faster, with an AI that actually reads the resume.

An applicant tracking system built around the way Indian companies hire. A 4-stage AI screening pipeline scores every applicant on six default parameters plus unlimited per-organisation custom ones, and offers go out under an OTP-verified digital signature with a complete audit trail.

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From requisition to offer

A six-stage pipeline, every step accounted for.

Open a role and post once across LinkedIn, Naukri, Indeed and your own career page (an embeddable widget you drop on your domain). Inbound resumes are parsed and scored. The pipeline tracks every candidate through applied → interview → pre-onboarding → BGI → offer → hired, with branches for rejected, on-hold, abandoned and not-interested.

  • AI-scored shortlists. Six default parameters plus unlimited per-organisation custom ones. Primary-skill rule caps anyone missing the must-have at 40 of 100.
  • Interviews, scheduled by HR. Multi-round, with Google Calendar availability checked one-way before booking. External panellists can review and submit feedback through a token-gated link without logging in.
  • Fraud signals during screening. Paste percentage, time-to-answer and tab-switches produce a LOW / MEDIUM / HIGH threat level visible to admins.
  • Offers from the same screen. Branded templates, OTP-verified digital signature on a token-protected page, IP, user-agent and timestamp captured.
Job · req 2418
Senior Backend Engineer · Bengaluru
AI ranked · 142 applicants
AM
Aarav Mehta
via LinkedIn
94/100
Strong
PN
Priya Nair
via Naukri
88/100
Strong
RS
Rohan Sharma
via Internal
76/100
Good
IB
Ishita Banerjee
via Referral
71/100
Good
KS
Kabir Singh
via Indeed
58/100
Average
The AI

A 4-stage pipeline. Six parameters. Reasoning visible.

Stage 1 filters non-resumes (invoices, articles, off-topic submissions) before the expensive scoring step runs. Stage 1.5 normalises and matches skills against the JD's required skills, with a primary-skill rule. Stage 2 applies six weighted scoring parameters: experience 30%, technical 20%, education 15%, domain 15%, stability 12.5%, resume quality 2.5%. Stage 3 thresholds determine reject / HR review / auto-advance.

  • Reasoning visible to admins. Each parameter has a justification logged with the score. Decision rationale is never shown to candidates.
  • Per-organisation custom parameters. Add as many as you need, set their weights so the total reaches 100%. The custom parameters are the biggest differentiator versus rigid black-box ATS scorers.
  • Anti-hallucination skills extraction. The model only extracts skills the resume actually mentions, with normalisation: React.js = ReactJS = react, C++ and C# treated correctly.
  • Test mode + cheat-code for evaluation. Run mock AI for free during evaluation. Org-controlled bypass for demos and pilots.

Today the pipeline is English-only and works on text-based PDF and DOCX resumes. OCR for scanned resumes and multi-language parsing are on the roadmap. We do not run a fairness / bias audit yet, so we won't claim it.

Security and isolation

Schema-per-tenant. Token-gated candidate UX. Comprehensive audit logs.

The ATS isolates customers at the PostgreSQL schema level, one schema per tenant, addressed by subdomain. Candidates never need a login: every candidate-facing action (screening, document upload, offer signing, referral submission) runs through a token-protected public page with an expiry per token type.

  • Schema-per-tenant isolation. Stronger than the row-level filtering most multi-tenant SaaS uses on a shared table. A bug in a query is far less likely to leak across tenants.
  • JWT + TOTP MFA + SSO. Email and password with bcrypt. TOTP MFA available. Google and Microsoft OAuth supported. JWT access tokens with 24-hour life, refresh tokens with 30-day life.
  • Audit log with threat-level tags. Every action recorded, categorised LOW / MEDIUM / HIGH across nine event types. Export to CSV.
  • 424 endpoints, all permission-gated. Granular custom roles per organisation, with an AI assistant that generates a permission set from a job description.

SAML, SCIM, SOC 2 / ISO 27001 attestations and DPDP right-to-be-forgotten endpoints are on the roadmap, not in current release. Today candidate data follows your retention policy via manual cleanup.

Tenant security · ATS
Per-customer schema isolation
Audit-logged
Tenancy model
PostgreSQL schema-per-tenant
Live
Auth
JWT + TOTP MFA + SSO
Live
JWT access token TTL
Refresh: 30 days
24 hours
Audit log categorisation
9 event types
LOW / MED / HIGH
Candidate UX
Token-gated, no login
Token / OTP
Roadmap
SAML / SCIM / SOC 2
Q3 / Q4
Interviews · multi-round
Interview scheduling
Embedded video
Multi-round configuration
Defined per role on the Job
Live
Embedded video room
Google Meet or Microsoft Teams
From candidate page
Reminders
Email · 1 hour before slot
Auto
External panellist review
Token-gated, no login
InterviewViewToken
Calendar sync
One-way availability check (Google)
Outbound only
Interview scheduling

Multi-round, calendar-aware, recruiter-managed.

A recruiter selects a slot, the system checks Google Calendar availability for the panel, sends the invite, books the meeting room. Embedded Google Meet or Microsoft Teams launches from the candidate page. External panellists can review and submit feedback through a token-gated link without an account.

  • Per-role rounds. Configure how many rounds a job needs and which panellists they go to. Conflict detection during booking.
  • Email reminders. Automated dispatch ahead of every interview, sent to candidate, HR and panellists.
  • External panellist tokens. Send a link, panellist reviews the candidate and submits feedback. No login.
  • Google Calendar one-way. Availability is read before booking. Two-way sync (block calendar on book) is on the roadmap.

Today HR picks the slot. Calendly-style self-serve candidate scheduling is on the roadmap.

Screening integrity

Fraud signals during AI screening, with admin-only visibility.

During the AI-driven screening (resume + question chat with default 25-minute timer), the system captures behavioural signals: paste percentage, time-to-answer per question, tab-switch counts and AI-content patterns. These produce a LOW / MEDIUM / HIGH threat level visible to admins, never to candidates.

  • Behavioural signals. Paste percentage, time-to-answer, tab-switch counts. Surfaced to admins as a threat level.
  • AI-content patterns. Detection signals fed into the same threat-level rollup.
  • Adaptive interview questions. Auto-generated per resume: verification, technical, behavioural and email-writing question types.
  • Custom feedback forms. Drag-drop builder with sections, field types, validation, conditional logic, undo. Clone forms across jobs.

No camera, microphone or screen capture proctoring. No public-web plagiarism fingerprint check. Those would require dedicated proctoring vendor integration; not in current release.

Screening · admin view
Behavioural signals
Threat level: LOW
Paste percentage
Across all answers
8%
Time-to-answer
Across 12 questions
Median 47 sec
Tab-switches
During the timed session
2
AI-content pattern
Per-answer detection
No matches
Default screening timer
Configurable per organisation
25 min
Visibility
Decision rationale
Admin only
Offer · Aarav Mehta
₹28,40,000 CTC
e-Signed 18 Apr
₹28.40 L Annual CTC
Basic + DA
50% of CTC, drives PF + gratuity
₹14,20,000
HRA
40% of basic, metro-eligible
₹5,68,000
Special allowance
Balancing component
₹4,82,400
Employer PF
12% of basic, statutory
₹1,80,000
Gratuity provisioning
4.81% of basic, annual accrual
₹68,000
Performance variable
Annual, paid quarterly
₹4,21,600
Offer letters

Branded templates. OTP-verified signature. Audit trail.

A four-step generation flow: payroll structure → template selection → generate letter → approval. Build CTC components (basic, HRA, DA, allowances, deductions, tax components). Place merge fields for candidate name, salary, joining date and CTC breakdown. The generated record persists with status (draft / sent / signed / rejected / expired) and produces a PDF on completion.

  • Per-organisation templates. Create, edit, copy, delete via the UI. Merge fields fill at generation. Preview before send.
  • OTP-verified digital signature. Token-protected public page. OTP delivered to candidate email. Digital-signature timestamp, IP and user-agent stored on the audit record.
  • Separate offer-approval gate. Offer letters go through their own approver before they're sent to the candidate.
  • BGI as a first-class pipeline stage. A pre-onboarding → BGI → offer flow with document upload, manual approval, and dedicated bgi_report_* document categories.

Today the digital signature is in-house (OTP + audit trail). DocuSign, Adobe Sign and NSDL eSign are not integrated. Background check vendor APIs (AuthBridge, IDfy, SterlingCheck, Checkr, HireRight) are also not in current release; vendors upload BGI reports manually through the candidate document portal.

Sourcing channels

Post once. Replies land in the same inbox.

Live connectors with LinkedIn, Naukri, and Indeed. Post once, replies come back into the same inbox.

Live

LinkedIn

OAuth-connected posting + reply parsing. Free and sponsored slots, both syndicated from one form.

Live

Naukri

India's largest job board. API-key connected. Resume database lookup on Premium tiers.

Live

Indeed

Domestic and international postings, plus optional sponsored boost from the same job form.

Frequently asked

ATS by pPulse.

Three live integrations today: LinkedIn (OAuth), Naukri (API key), Indeed (API key). Plus an embeddable career widget you drop on your own site, with impression and apply tracking. We also generate XML feeds per portal (Indeed, Google Jobs, generic) for aggregator pickup. Glassdoor, Monster, ZipRecruiter, AngelList / Wellfound, Hirist, Cutshort and Hirect are not in current release. We won't claim them until they ship.
Yes. Each scoring parameter has a justification logged with its sub-score, visible in the admin candidate detail view. Decision rationale is never shown to candidates. We don't currently run a fairness or bias audit on the model, so we won't claim "bias-aware by design"; this is on our research roadmap.
Not via a native integration today. The ATS includes its own custom feedback form builder (drag-drop with sections, field types, validation, conditional logic, undo) plus AI-generated interview questions. HackerRank, HackerEarth and Mettl integrations are on the roadmap.
PostgreSQL schema-per-tenant isolation, addressed by subdomain. JWT and TOTP MFA on staff logins; candidate flows are token-gated public pages with no candidate login. We don't have automated DPDP / GDPR right-to-be-forgotten endpoints today; deletion is handled manually on request. SOC 2 / ISO 27001 attestations are on the roadmap.
Token-gated public OfferLetterSigning page (no candidate login). OTP delivered to the candidate email, then the candidate signs. Timestamp, IP and user-agent recorded against the offer record for audit. Status flips to "signed" on completion and a final PDF is generated. The signature is in-house: it isn't NSDL eSign / Aadhaar e-Sign / DocuSign yet, so legal enforceability depends on jurisdiction.
Templates use merge fields and the four-step generator: payroll structure → template selection → generate letter → approval. Build CTC components (basic, HRA, DA, allowances, deductions, tax components) once per organisation; the offer letter renders them per candidate. Indian tax-slab calculator is not yet built into the offer letter; tax computation is component-driven.

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