Verification Engine
Land Record DigitizationOwnership VerificationCrop History TrackingLoan Eligibility ScoringPortfolio Risk Analytics
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Stage 01 · Digitize

Land records converted into a structured, searchable ledger.

Paper registers, PDF exports, and half-digitized portal records are parsed into a normalised parcel record: owner, survey number, area, boundary points, and the full mutation trail.

Parcel record after digitization
OwnerRamesh K.Extracted
Khasra / Survey142 / 3BExtracted
Area2.4 acresExtracted
Boundary6 survey points capturedExtracted
Mutation trail3 mutations since 2011Extracted
Confidence0.94 average across fieldsOK
Worked example

One paper RTC in, one structured record out.

A single record shown end-to-end. Real records vary by state and region - the shape below is representative, not universal.

IN

Source document

A scanned Record of Rights, in the local language, with a handwritten mutation note in the margin.

filename: rtc_142_3B.pdf
pages: 2 · language: hi-IN, en
handwriting: present
OUT

Structured record

A single JSON-shaped parcel object with named fields, confidence per field, and source-page anchors preserved for audit.

fields: 12/12 extracted
low-confidence: 0 flagged
anchors: preserved
Honest note

Where digitization is strong, and where it needs review.

Where the platform is confident and where it is not - stated plainly, on the surface, not buried in a data sheet.

Typed and cleanly-scanned government records extract reliably, with per-field confidence available on the record itself. Handwritten margin notes, faded stamps, and multi-language mixed layouts drop confidence and are flagged for a human check before the parcel record is marked complete.

Every extracted field carries a source-page anchor - the underwriter can click any value in the parcel record and see the exact patch of the original document it came from.

Next in the sequence
Ownership Verification