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Tech · IDP_PIPELINE_AGENT

Intelligent Document Processing Agent

Extract, classify, and route unstructured documents at scale

Combines OCR, layout understanding, and field extraction for invoices, purchase orders, onboarding packets, and customs forms — with validation rules and ERP handoff.

Business problem

Operations teams manually re-key data from PDFs and scans, introducing errors and backlog that delay payments, shipments, and compliance filings.

Intended users

  • Accounts payable and receivable teams
  • Logistics coordinators processing customs paperwork
  • HR operations handling onboarding document packets

Key outcomes

  • Automated classification of inbound document types with routing rules
  • Field-level extraction with confidence scores per line item
  • Exception queues for low-confidence or non-standard layouts
  • Straight-through posting to ERP or accounting systems when thresholds pass

Visual workflow

workflow / agent-pipelineIllustrative
  1. 01

    Input

    Documents arrive via email inbox, SFTP drop, API upload, or scanner integration with MIME type and origin metadata.

  2. 02

    Agent

    Layout-aware models classify the document, extract entities (vendor, PO number, line items, dates), and normalise formats.

  3. 03

    Validation

    Business rules cross-check totals, duplicate invoice detection, vendor master match, and mandatory field completeness.

  4. 04

    Human Review

    Exceptions surface in a review UI with side-by-side PDF highlighting; reviewers correct fields and approve or reject.

  5. 05

    Action

    Validated records post to ERP, trigger approval workflows, or generate payment files per your finance policies.

  6. 06

    Record

    Original file, extraction JSON, reviewer edits, and downstream transaction IDs are archived for audit retrieval.

Inputs

  • PDF, TIFF, PNG, and multi-page scan batches
  • Vendor and SKU master data for matching
  • Document-type templates and field schemas
  • Validation thresholds per document category

Outputs

  • Structured JSON or CSV extraction payloads
  • Exception worklists with SLA timers
  • ERP-ready transaction stubs
  • Processing throughput and accuracy reports

Integration categories

ERP & accounting systemsEmail and file ingestionCloud object storageApproval workflow tools

Human review points

  • Extractions below per-field confidence thresholds
  • New vendor or unseen document layouts
  • Amount mismatches against PO or contract limits

Security & data handling

  • Documents encrypted at rest with customer-managed keys optional
  • Processing regions configurable for data residency
  • Retention policies auto-purge raw files after archival period

Deployment process

  1. Sample 50–100 representative documents per type
  2. Train extraction templates and calibrate confidence thresholds
  3. Connect ERP sandbox and run parallel validation
  4. Go live with exception-only human review, then tune STP rate

FAQ

What accuracy can we expect on invoices?

Results vary by layout consistency; most clients achieve high straight-through rates on standard vendor templates after a calibration sprint.

Does it support handwritten fields?

Printed and typed text is primary; handwritten annotations can be flagged for human review depending on scan quality.

Can we add new document types later?

Yes. New schemas deploy through a staging environment with labelled samples before production promotion.

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