DocDhara Platform
Deploy IDP Suite
INTELLIGENT DOCUMENT PROCESSING HUB

DocDhara Platform Overview

A modular suite of AI pipeline capabilities built to turn complex, unstructured formats into audit-ready structured tables. Fully deployable inside your private cloud perimeter.

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01 . Core Parsing Engine

AI-Driven Data Extraction

Extract high-confidence key-value pairs from complex, unformatted PDFs and images. DocDhara uses advanced OCR encoders coupled with semantic models to parse labels instantly, calculating verification checksums automatically.

99.4% average straight-through extraction rate.
Auto-identifies vendor information, balance totals, and line item tables.
VPC-native containment guarantees zero telemetry leaking.
Explore DocDhara Extraction
Visual Bounding Box MatcherHover elements to trace schema
COMMERCIAL INVOICE

Vendor

Acme Industrial LLC

Invoice #

INV-2026-904

Summary Rate

Total Amount:
$3,240.00
Vendor99.8%
"Acme Industrial LLC"
Invoice ID99.9%
"INV-2026-904"
Total Due99.5%
"$3,240.00"
Auto-Preprocessing NodeReady
DeskewContrastClassify
console ready. click run pipeline to test.
02 . Document Alignment

Auto-Preprocessing

Unnormalized documents are the primary cause of downstream OCR extraction errors. DocDhara integrates a localized pipeline agent that checks skew angles, auto-rotates pages, normalizes pixel contrast (deskewing and binarization), and crops raw scan borders.

Dynamic deskewing rectifies scanned documents tilted up to 45 degrees.
Binarization and contrast filtering ensure dark ink isolation.
Smart classification auto-routes folders to matching extraction queues.
Explore Document Pipelines
03 . Ready-to-Use Weights

Pre-trained Models

Skip the annotation loop and start extracting data from day one. DocDhara features over 30 out-of-the-box pre-trained schemas configured for standard operational files like commercial invoices, bank statements, tax forms, and utility statements.

No model annotation training required for standard formats.
Pre-loaded with deep verification checklist logic.
Active fine-tuning adjustments allowed on top of existing layers.
Browse Pre-trained Models
Commercial Invoice Model
Acc: 99.4%Latency: 1.2s
Fields Extracted
•Vendor Name
•Tax ID
•Line Items (Qty, Desc, Rate, Amount)
•Total Due
•Due Date
Output JSON Schema
{
  "document_type": "COMMERCIAL_INVOICE",
  "vendor": { "name": "string", "tax_id": "string" },
  "line_items": [{ "desc": "string", "qty": "number", "rate": "number" }],
  "totals": { "tax_total": "number", "grand_total": "number" }
}
Line-Item Table EditorDouble click cell to edit values
DescriptionQtyRateAmount
AI Ingestion Engine2$400.00$800.00
OCR Pipeline Node1$1,200.00$1,200.00
Validation Telemetry Client5$150.00$750.00
04 . Complex Spatial Mapping

Smart Table Extraction

Extracting grid arrays and multi-page tables requires spatial coordinate understanding rather than flat text OCR reading. DocDhara identifies row/column boundaries, aligns nested descriptions, and stitches multi-page tables together into a single structured spreadsheet array.

Extracts borderless and nested tables with high row coordinate accuracy.
Stitches tables split across multiple pages seamlessly.
Outputs structured data immediately into clean CSV, XLSX, or API arrays.
Explore Table Extractions
05 . Validation Perimeter

Human-in-the-loop Review

Keep validation checklists airtight. If the extraction model encounters a low-confidence field, a calculation error, or a mismatched database entry, it flags the document for human review. It displays side-by-side highlighting, enabling quick visual audits before exporting.

Flags only the fields requiring human intervention, minimizing manual search.
Enforces mathematical validations (e.g. tax sums and unit matches).
Active learning loop feeds corrections back to retrain the local weights.
See HITL Pipelines
HITL Review Verification ScreenNeeds Action

Tax Mismatch Error

Extracted Tax Total is $240.00, but sum of line item taxes is calculated as $300.00. Please check and correct the field.

Field ID:tax_total
Raw Value:$240.00
Ingested: Acme_Invoice_904.pdf
Rule Engine: Tax validation rule triggered.
Alert: Line item tax sum ($300.00) != extracted Tax Total ($240.00).
GyanDhara Tuning WorkbenchInactive
Tuning Loss Curve
Val Accuracy (%)
training unit ready. click run training pipeline...
06 . Few-Shot Fine-Tuning

Train Custom Model

Deploy customized extraction weights configured for proprietary schemas. With GyanDhara integration, operations teams can upload as few as 20 annotated document samples to train, evaluate, and deploy customized OCR-LLM checkpoints in hours, avoiding massive dataset prerequisites.

Few-shot annotation allows rapid deployment on 20 examples.
Localized validation telemetry safeguards custom endpoints.
Outputs weights directly into secure, custom private S3 volumes.
Train Custom Models

VPC-Native Isolation: You Control Your Data

Unlike typical cloud-based OCR products, the SangamBytes platform is built from the ground up to deploy completely inside your secure Virtual Private Cloud (AWS, Azure, Google Cloud) or on-premise hardware. Under this perimeter, no raw scans or extracted schema data ever leave your firewall.

VPC Storage Containment

Direct mounting onto private buckets (S3, GCS, Blob). Scans are read, processed, and destroyed inside memory perimeters.

Audit Logs Compliance

Complete audit records matching ISO 27001, SOC2, HIPAA, and DPDP frameworks. Zero tracking telemetry to external servers.

Dedicated Inference Node

Custom models are loaded onto localized GPU compute threads, bypassing shared multi-tenant rate limits.

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