Document AI · OCR · Data Extraction

DocStream — Paperclip Document Automation

$8,000–$15,000 implementation
+ $2,500/month retainer · any document format · 95%+ extraction accuracy

DocStream processes contracts, invoices, forms, and insurance documents automatically — including the messy, unstructured PDFs that rule-based OCR tools fail on 30–40% of the time. Claude AI understands document semantics, not just character recognition, which is why it extracts the indemnification clause limit even when it's phrased twelve different ways in twelve different contracts.

95%+
Extraction Accuracy
Any
Document Format
$8,000
Starting Price

The Manual Document Processing Tax

Finance teams in growing companies spend an average of 15–20 minutes manually keying data from each invoice into their accounting system. At 50 invoices per day, that's 12–17 hours of AP staff time — every day — doing a task with no strategic value and a high error rate.

Legal teams read every contract before a deal closes. The average enterprise contract is 40–80 pages. A paralegal at $60/hour reading and summarizing a 60-page contract spends 3–4 hours on it. If you close 20 deals a month, that's 60–80 hours of paralegal time per month, plus attorney review time on top.

Insurance companies triage hundreds of claims per day. Each claim requires a human to read it, classify it, and route it to the right adjuster. The manual triage process takes 8–12 minutes per claim. The cost is not just the time — it's the bottleneck it creates downstream in the claims pipeline.

The Math

15 minutes per document × 200 documents/day × $25/hour burdened labor cost = $1,250/day or $325,000/year in manual document processing labor. DocStream implementation at $10,000 + $2,500/month retainer = $40,000/year. ROI: 8x return in year one.

How DocStream Works

A four-stage pipeline from raw document to structured action — configured for your document types and target systems.

Intake

Documents enter DocStream through any configured channel: email attachment monitoring (Gmail or Outlook API), a branded upload portal, or cloud storage sync (Amazon S3, SharePoint, or Google Drive folder watch). Multiple intake channels can run simultaneously — an invoice can arrive by email while a contract arrives via the upload portal; both are processed through the same pipeline. Supported formats: PDF (native and scanned), DOCX, XLSX, image files (JPG, PNG, TIFF).

Classify

Claude AI reads the document and determines: document type (invoice, contract, insurance claim, HR form, purchase order, loan application), sub-type where relevant (NDA vs. service agreement vs. employment contract), urgency classification if configured (routine, expedited, exception), and any configured priority flags (e.g., "invoices over $50,000" → escalated routing). Classification happens in seconds per document regardless of page count.

Extract

Claude extracts your defined field schema as structured JSON. For invoices: vendor name, invoice number, date, line items, amounts, tax, payment terms. For contracts: parties, effective date, termination rights, liability limits, payment terms, IP ownership, governing law. For insurance claims: claimant, policy number, incident date, damage description, coverage category. The extracted JSON is validated against your schema, confidence-scored, and flagged for human review if below your configured threshold.

Route

Based on document type and extracted fields, n8n routes the structured data to its destination: CRM record update, ERP line item creation, task assignment in your project management system, Slack notification to the responsible team, exception queue for human review, or direct email with the extracted summary attached. High-confidence extractions route automatically. Low-confidence or exception documents go to a human review queue with the document and extracted fields side-by-side for fast approval.

Document Types We Handle

DocStream is configured for your specific document types during implementation — the list below represents our pre-built extraction schemas. Custom document types are scoped and priced during discovery.

Invoices Contracts Insurance Claims Loan Applications HR Forms Purchase Orders Medical Records Real Estate Docs Custom Types

Why Not Just Use OCR?

Traditional OCR tools convert image pixels to text. They don't understand what they're reading. Claude does.

Challenge DocStream (Claude AI) Traditional OCR
Handwritten annotations Claude reads context to interpret Fails on non-standard handwriting
Unstructured layout (no fixed fields) Semantic understanding, any layout Requires template per document format
Context-dependent field extraction Extracts "indemnification limit" regardless of phrasing Keyword matching only — misses variations
Multi-page complex documents Reads full document with 200k context ~ Page-by-page, no cross-page reasoning
Document type classification Classifies by understanding content Requires pre-sorted input
New vendor / new format without re-training No re-training needed New template required per format

Common Questions

Can you guarantee extraction accuracy?
We benchmark accuracy during the validation phase before production deployment. For well-defined document types (invoices, standard contracts), DocStream consistently achieves 95–99% field-level accuracy. For less structured documents (insurance claims, medical records), accuracy is typically 88–95% with confidence scoring to flag lower-confidence extractions for human review. We do not quote accuracy guarantees before seeing a sample of your actual documents — any vendor who guarantees 99% on document types they haven't tested is not being honest with you. We run a free sample extraction on 20–30 of your real documents before you sign.
How does DocStream handle multi-page complex documents?
Claude's 200,000 token context window can hold approximately 150,000 words — roughly a 600-page document. For practical purposes, this means DocStream can read an entire complex contract, lease, or loan application in a single context without chunking. Chunking (splitting documents into pieces for shorter context models) is the primary source of cross-page extraction errors in traditional OCR and GPT-4-based document AI tools. DocStream avoids this entirely for documents under ~500 pages. For document batches exceeding this (rare), we use a two-pass architecture: section-level extraction followed by a reconciliation pass.
Can DocStream integrate with our existing document management system?
Yes. DocStream integrates with SharePoint, Google Drive, Box, Dropbox, DocuSign, NetDocuments, iManage, and most document management systems via their REST APIs. For systems with limited API access, we can integrate via email (document arrives as attachment, DocStream processes it, result is sent back) or SFTP drop. Integration with your ERP or accounting system for the downstream write (QuickBooks, NetSuite, SAP, Oracle, Xero) is scoped during discovery — most major systems have either a native n8n node or a well-documented REST API.
Is DocStream HIPAA and SOC 2 compliant?
In the self-hosted deployment model, yes. Medical records, insurance claims, and other PHI-containing documents never transit Tiboh infrastructure — they flow directly from your intake channel to the Claude API (which supports HIPAA BAA for enterprise accounts) to your n8n instance to your database. For HIPAA specifically, we document the complete data flow architecture, configure zero-retention on the Claude API, and do not log PHI in n8n execution history. For SOC 2 Type II audits, we provide architecture diagrams, data flow documentation, and audit log configuration that meets most auditor requirements. Healthcare clients receive a compliance-specific implementation variant at no additional cost.

Stop Paying People to Read Documents. Start Routing the Decisions.

DocStream processes any document format with 95%+ accuracy and routes the structured data where it needs to go — automatically, auditably, at scale.

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