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Document Processing — Automate Document Workflows

GPU-accelerated OCR, AI entity extraction, multi-format classification, and compliance-grade audit trails. Documents processed, not just scanned.

Document Processing: Automate Document Workflows

Documents processed in seconds, not days. With full audit trail.

Every enterprise has a document problem. Insurance claims arrive as PDFs, photos, and faxes. Financial statements come in 47 different formats. Compliance documents need extraction, classification, and routing — and the penalties for errors are measured in regulatory fines, not inconvenience.

Boggess AI's document processing pipeline combines GPU-accelerated OCR, AI-powered entity extraction, multi-format classification, and workflow routing into a single system that handles documents the way your best analyst would — except it runs 24/7, never makes transcription errors, and maintains a compliance-grade audit trail for every document it touches.

The Document Bottleneck

Manual document processing is the hidden tax on enterprise operations:

  • Average processing time: 8-12 minutes per document for manual data entry
  • Error rate: 4-6% for manual data entry (industry average)
  • Straight-through rate: Less than 15% of documents processed without human touch (typical enterprise)
  • Compliance risk: Missing or misfiled documents account for 23% of regulatory findings

Key Features

1. GPU-Accelerated OCR

Optical character recognition running on GPU infrastructure handles document volumes that CPU-based solutions cannot match:

  • Throughput: 8x peak volume capacity with horizontal scaling on Kubernetes
  • Accuracy: 99.2%+ character accuracy on clean documents, 97%+ on degraded scans
  • Format support: PDF, TIFF, JPEG, PNG, BMP, HEIF, and scanned document images
  • Preprocessing: Automatic deskew, noise reduction, contrast enhancement, and orientation correction
  • Language support: English, Spanish, French, German, Portuguese, and CJK character sets

2. AI Entity Extraction

Beyond OCR — understanding what the document says:

  • Named entity recognition: Amounts, dates, names, addresses, policy numbers, claim numbers, account numbers
  • Relationship extraction: Connecting entities within a document (e.g., "this amount relates to this claimant at this address")
  • Table extraction: Structured data from tabular content (financial statements, rate schedules, claim summaries)
  • Handwriting recognition: AI-assisted extraction from handwritten notes and forms
  • Confidence scoring: Every extracted entity tagged with confidence score for human review thresholding

3. Multi-Format Document Classification

Automatic classification routes documents to the correct workflow:

Document Type Classification Confidence Routing
Insurance claim forms 98.5% Claims processing pipeline
Financial statements 97.8% Financial analytics engine
Compliance certificates 96.2% Compliance tracking system
Invoices and receipts 99.1% Accounts payable workflow
Legal correspondence 95.4% Legal review queue
Medical records 97.3% Medical review + HIPAA handling

The classifier is trained on your document types. Initial training requires 50-100 labeled samples per category; accuracy improves continuously with production feedback.

4. Straight-Through Processing

Documents that meet confidence thresholds flow through without human touch:

Document Received
    |
    v
Classification (>95% confidence?)
    |--- No ---> Human Review Queue
    |--- Yes --->
    v
Entity Extraction (all required fields >90% confidence?)
    |--- No ---> Human Review Queue
    |--- Yes --->
    v
Validation (business rules pass?)
    |--- No ---> Exception Queue
    |--- Yes --->
    v
Routing (to downstream system)
    |
    v
Audit Log (complete chain of custody)

Target: 70%+ straight-through rate on routine document types within 30 days of deployment. Complex or degraded documents always route to human review.

5. Workflow Routing Engine

Configurable routing rules that connect document processing to downstream systems:

  • Rules engine: IF document_type = "claim" AND amount > 10000 THEN route to "senior_adjuster_queue"
  • Priority assignment: Urgency derived from document content (e.g., regulatory deadlines, claim severity)
  • Parallel routing: Document can be sent to multiple destinations simultaneously
  • Escalation: Documents in queue beyond SLA threshold auto-escalate
  • Integration hooks: Webhook notifications for downstream system consumption

6. Compliance-Grade Audit Trail

Every document maintains full chain of custody:

  • Receipt timestamp: When the document entered the system
  • Processing log: Every OCR pass, extraction attempt, classification decision
  • Confidence scores: Per-entity confidence at time of extraction
  • Human review log: Who reviewed, what they changed, when
  • Routing history: Where the document went and when
  • Retention policy: Configurable per document type and jurisdiction
  • Export: Full audit trail exportable for regulatory examination

7. Check Processing (CheckSmart)

Specialized pipeline for check and payment document processing:

  • MICR line extraction: Magnetic Ink Character Recognition for routing and account numbers
  • Amount verification: Written amount vs. numeric amount cross-validation
  • Signature detection: Presence/absence of signature (not forgery detection)
  • Duplicate detection: Hash-based deduplication across processing windows
  • Straight-through deposit: Qualified checks processed without manual review

8. API-First Architecture

Every capability accessible programmatically:

# Submit document for processing
response = requests.post("/api/v1/documents", files={"file": open("claim.pdf", "rb")})
document_id = response.json()["document_id"]

# Check processing status
status = requests.get(f"/api/v1/documents/{document_id}/status")

# Retrieve extracted entities
entities = requests.get(f"/api/v1/documents/{document_id}/entities")

# Download processed output
output = requests.get(f"/api/v1/documents/{document_id}/output")

Architecture Overview

+-------------------+     +-------------------+     +-------------------+
| Email Ingestion   |     | API Upload        |     | Scan/Fax Gateway  |
+--------+----------+     +--------+----------+     +--------+----------+
         |                         |                         |
         +-------------------------+-------------------------+
                                   |
                    +--------------+--------------+
                    |     Document Ingestion      |
                    |  Format detection, dedup,   |
                    |  preprocessing              |
                    +--------------+--------------+
                                   |
                    +--------------+--------------+
                    |     GPU OCR Cluster         |
                    |  Kubernetes-scaled,         |
                    |  8x peak capacity           |
                    +--------------+--------------+
                                   |
                    +--------------+--------------+
                    |     AI Processing           |
                    |  Classification, entity     |
                    |  extraction, validation     |
                    +--------------+--------------+
                                   |
                    +--------------+--------------+
                    |     Routing Engine          |
                    |  Rules, SLA, escalation     |
                    +--------------+--------------+
                                   |
              +--------------------+--------------------+
              |                    |                    |
     +--------+-------+  +--------+-------+  +--------+-------+
     | Claims System  |  | Financial Sys  |  | Compliance     |
     +----------------+  +----------------+  +----------------+

Integration Points

System Method Capability
Email (Outlook/Graph) Graph API Inbound document ingestion from email
MinIO S3-compatible Document storage with versioning
PostgreSQL + pgvector Direct Document metadata, embeddings for search
Downstream APIs REST webhooks Routing processed documents to business systems
ORAC Platform MCP Cross-platform orchestration and monitoring

Use Cases

Insurance Operations: Claims documents — photos, police reports, medical records, repair estimates — processed and routed to the correct adjuster queue within minutes of receipt. AutoCSR integration for end-to-end claims automation.

Financial Services: Statement processing, check handling, invoice extraction. DuPont and Healy-Palepu analysis triggered automatically when financial statements are processed.

Legal and Compliance: Contract extraction, regulatory filing classification, compliance certificate tracking. Full audit trail for regulatory examination.

Healthcare: Medical record processing with HIPAA-compliant handling. Entity extraction for clinical data (diagnoses, procedures, medications) with de-identification.

Call to Action

Your documents are sitting in queues. Let them flow.

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