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Rivac AI Labs
Computer Vision & Voice AI Solutions

OCR & Document Image Data Extraction

Every business with paper or scanned-document volume (invoices, receipts, applications, intake forms) eventually hits the same wall: someone is retyping that data into a system by hand, and it's slow, error-prone, and doesn't scale. This service builds an extraction pipeline tuned to your specific document types, pulling the exact fields you need into clean, structured data, even when the source documents are skewed scans, mixed layouts, or partly handwritten. It's not generic OCR, it's a pipeline that knows what an invoice line item or an application field looks like in your documents specifically, and flags anything it isn't confident about instead of silently guessing. The result is a data-entry job that used to take hours turned into a review queue that takes minutes.

This is a capability we deliver for you as a service, not a role we’re hiring for.

How We’d Approach This

A clear, staged plan, not a black box

These are the service-specific steps inside our six-step process.

  1. 1

    Diagnose: gather a representative batch of your real documents, across the messiest formats and quality levels you actually see, and define the exact fields to extract.

  2. 2

    Pilot: build an extraction pipeline for one document type and run it against a batch of historical documents with known correct answers.

  3. 3

    Review: check extracted fields against ground truth, and tune the pipeline for the specific layouts, fonts, or handwriting causing errors.

  4. 4

    Build: harden the pipeline with validation rules, a confidence-scored human-review queue for exceptions, and a connection into your existing storage or system of record.

What You Get

Deliverables from this engagement

  • A configured extraction pipeline for your specific document types and fields
  • A structured data output feed (CSV, JSON, or database rows) ready for your existing systems
  • A confidence-scored review queue for extractions that need a human check
  • An accuracy benchmark report against manually verified samples
  • Integration into your existing storage, CRM, or ERP system

Six Ways We Could Architect This

Different engagement, different build, pick the shape that fits

There’s more than one way to deliver on this service. Browse a few of the ways we’d structure the work, depending on your speed, budget, and integration needs.

Read all 6 architectures as text

Lean Fast-Start Architecture

Intake

  • Scanned Document Uploaded
  • Basic Image Preprocessing
  • Off the Shelf OCR Engine

Field Extraction

  • Template Based Field Mapping
  • Extracted Fields Draft

Validation

  • Confidence Acceptable
  • Sent to Manual Review Queue
  • Auto Accepted

Output

  • Reviewer Corrects Fields
  • Structured Data Saved
  • Data Exported to Spreadsheet

Cloud-Native / Managed Services Architecture

Intake

  • Document Upload Portal
  • Cloud Object Storage
  • Managed OCR Service

Extraction Layer

  • Managed Document Understanding API
  • Field Extraction Model
  • Structured Data Store

Review Layer

  • Confidence Score Check
  • Managed Review Queue Interface
  • Auto Approved Record
  • Reviewer Confirms Fields

Delivery Layer

  • Synced to Business Database
  • Managed Analytics on Extraction Accuracy

Event-Driven & Automation-First Architecture

Triggers

  • Document Dropped in Watched Folder
  • Ingestion Event Fired
  • Email Attachment Received

Automation Layer

  • Preprocessing Job Queue
  • OCR Extraction Worker
  • Field Parser
  • Confidence Threshold Met
  • Auto Posted to Downstream System
  • Review Task Created and Assigned

Review Loop

  • Reviewer Corrects in Queue App
  • Correction Logged as Training Signal

Outcome

  • Record Available in ERP or Accounting
  • Extraction Accuracy Metric Updated

Enterprise-Grade & Compliance-Ready Architecture

Governance

  • Document Handling Policy
  • Data Privacy and Retention Rules
  • Access Control Policy

Secure Pipeline

  • Access Controlled Document Repository
  • Encrypted Extraction Pipeline
  • Role Based Reviewer Access

Audited Extraction

  • Extraction Model with Versioned Rules
  • Every Field Change Logged
  • Sensitive Data Detected
  • Redaction and Compliance Check
  • Standard Processing Continues

Compliance Reporting

  • Audit Trail Export
  • Redundant Secure Archive
  • Quarterly Compliance Report

AI-Augmented, Human-in-the-Loop Architecture

Data In

  • Scanned Document or Image
  • Document Type and Layout Library

AI Extraction

  • AI Document Understanding Model
  • AI Extracted Field Values
  • Per Field Confidence Score

Human in the Loop

  • Any Field Below Threshold
  • Low Confidence Fields Highlighted for Reviewer
  • Reviewer Confirms or Corrects Fields
  • Correction Sent Back to Model as Feedback
  • All Fields Auto Approved

Output

  • Final Structured Record
  • Record Pushed to Business System

Integration-Heavy / Ecosystem-Connected Architecture

Client Systems

  • Accounting or ERP System
  • Extraction Orchestration Core
  • Document Management System
  • Email or Scanning Platform

Extraction Core

  • Document Classification Engine
  • Field Extraction and Mapping Layer

Sync Layer

  • ERP Record Creation Sync
  • Document Management Tagging Sync
  • Accounting Ledger Entry Sync

Governance Reporting

  • Processing Volume Dashboard
  • Straight Through Processing Rate Report

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Ready to get started?

Tell us what you’re trying to get done and we’ll help you find the highest-leverage place to start, scoped small enough to prove itself before you commit to anything bigger.

Talk to us about OCR & Document Image Data Extraction

Most engagements like this start as a $500–$2,500 pilot, see full pricing.

Questions? Book a free call