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Salary Slip Analyzer

AI
structured JSON of earnings + deductions + YTD with original component names preserved for YoY comparison.
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What you'll get: structured JSON with employer / employee / period / earnings / deductions / totals / YTD. Preserves idiosyncratic component names (Special Allowance, LTA, etc.) for accurate YoY comparison.

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Private & secure
AI tools process your PDF in memory, send only the extracted text to the model, and discard everything immediately. No file is persisted on our servers.
No watermarks
Clean output, no branding, no daily limits.
Pay only for what you use
Purchased credits never expire. Cancel anytime.

Why people use Salary Slip Analyzer

Indian salary slips have a fixed-but-varied structure: earnings (basic, HRA, special allowance, LTA, bonus) plus deductions (PF, professional tax, TDS, loan EMIs). Salary Slip Analyzer extracts all components into structured JSON with original component names preserved, so you can compare slips year-over-year or across employers without losing the original labeling.

Year-over-year comp tracking
Run each month’s slip through the analyzer, structured output goes into a spreadsheet. Real comp growth becomes visible (separating actual growth from inflation / role-change / variable-pay timing).
Job-change comp comparison
When comparing offers from multiple employers, run their slip samples through the analyzer to standardize the comparison. CTC pivots are misleading; component-level comparison reveals what actually hits in-hand monthly.
Tax planning prep (year-end)
Year-end tax planning needs accurate income breakdown. The analyzer extracts taxable / non-taxable components (HRA exemption, LTA, food coupons, professional development) so the CA has structured input rather than re-keying from PDF slips.
Loan application income proof
Lenders need 3 months of structured payslip data. The analyzer’s output is loan-application ready — pairs with the Loan Application Bundler Audit for the full pre-submission check.
ITR (Form 16 vs slips reconciliation)
Filing ITR requires slip components reconciled with Form 16. The structured output makes the reconciliation a one-pass verification — faster than month-by-month manual cross-check.

How Salary Slip Analyzer works

Three steps. Sign in to run, zero retention — files never persisted on our servers.

  1. STEP 1
    Drop the slip PDF
    PDF up to 25 MB. Works on Indian payslip formats (most ESS portal exports, payroll-vendor formats, paper slips that have been scanned and OCR’d).
  2. STEP 2
    We extract + structure
    Server-side extraction (OCR if needed), then structured parsing. Earnings components (basic, HRA, allowances, bonus, retention pay, variable pay) and deductions (PF, ESI, P-tax, TDS, voluntary deductions) extracted with original component names preserved — critical for YoY comparison where employers occasionally rename components.
  3. STEP 3
    Get JSON output
    Structured JSON: earnings breakdown / deductions breakdown / net pay / YTD totals. Original component names preserved (no canonicalization that would lose information). Importable into spreadsheets for tracking.

What makes pdfcraft ai different

  • Citations on every claim
    Every AI summary, answer, and translation links back to the page it came from. You can verify the source before relying on the output. Hallucination is bounded, not blind.
  • Pay only for what you use
    No subscription. Purchased credits never expire. Cancel anytime. Cost shown before you run — exact credit amount appears after upload.
  • Multi-provider routing, no vendor lock-in
    We balance multiple AI providers per call to optimise cost and quality. If one has an outage, the next call automatically tries another. You're not bound to a single vendor's pricing or downtime.
  • Zero retention by design
    Your PDF lives in memory only as long as the AI call needs it, then it's discarded — nothing is persisted to our servers. We don't fine-tune models on your data. Verifiable in your dashboard's audit log.
  • Honest about model limits
    When a doc exceeds the model's context window we surface that the output was truncated (we render result.wasTruncated in every AI tool's UI). When a number can't be verified from the source we flag it. No silent failures.

Frequently asked questions

Why preserve original component names instead of canonicalizing?
Indian employers vary wildly in naming (“Special Allowance” / “Performance Allowance” / “Variable Pay” / “Adhoc Allowance” can all be the same component or different). Canonicalizing into “allowance” loses the distinction. Preserving names lets you compare YoY meaningfully — if your “Special Allowance” renamed to “Variable Pay” mid-year, that’s a real signal worth keeping.
Does it calculate tax?
Surfaces the TDS deducted but doesn’t calculate optimal tax structure or recommend regime selection. For tax planning (old vs new regime, exemption planning, investment-driven deductions), use a CA or a tax-planning tool that takes the full picture (other income, deductions claimed, etc.).
Will it work for non-Indian payslips?
Indian slips primarily. US W-2 / paystubs, UK payslips, EU payslips work approximately but the component-classification heuristic is India-trained — results are less calibrated for other jurisdictions.
What about Form 16 / ITR documents?
Form 16 is structurally different (annual aggregate, not monthly slip). Drop a Form 16 and you’ll get a partial parse but not the full slip-level granularity. For ITR document analysis, dedicated tax tools are a better fit; this analyzer focuses on monthly slips.
What’s the credit cost?
3 credits per slip. Cost is fixed regardless of slip size.
Privacy?
Slip sent to inference provider for parsing, not stored. For maximum confidentiality (especially when sharing the structured output for loan applications or tax planning), redact PAN / Aadhaar / bank account numbers via Redact PDF first — the structural parse still works on the redacted slip.

Preparing a loan application?

Loan Application Bundler Audit verifies your loan documentation against the lender’s typical checklist — useful after the salary slip analysis for the “ready to submit?” check.

Try Loan Bundler Audit

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