Stop Manual Document Processing

A lab service provider sends an invoice for services rendered during a clinical trial, including details like invoice number, date, service descriptions, and the billed amount.

Document Processing

DocRouter.AI receives the invoice and, if necessary, converts the document into a machine-readable format.

Data Extraction

• Invoice number
• Vendor name
• Contract/reference number
• Invoice date
• Billed amounts and line-item details

Automated Verification

• Rate Verification: Compares billed rates against those specified in the contract
• Service Eligibility: Confirms that the billed services are covered under the contract
• Quantity & Billing Cycles: Ensures the invoiced quantities fall within agreed limits and that billing is aligned with contract terms

Shipping container manifests are critical documents that list all items loaded into a container. DocRouter.AI automates the extraction and verification of manifest data against physical inventory, dramatically reducing processing time and errors.

Document Processing

When a manifest is submitted (PDF, scan, or API), DocRouter.AI processes it to extract structured data that can be matched against inventory systems.

Key Data Extraction

• Container and seal numbers
• Shipping dates and route information
• Item descriptions and quantities
• Weights and dimensions
• Special handling instructions

Financial analysts and investors need to process large volumes of quarterly (10-Q) and annual (10-K) reports. DocRouter.AI automates the extraction of key financial metrics, risk factors, and business developments, enabling rapid analysis and comparison across multiple companies and time periods.

Document Processing

When reports are uploaded, DocRouter.AI processes both the structured (financial tables) and unstructured (management discussion, risk factors) sections to extract relevant information.

Key Data Extraction

• Financial statements and metrics
• Management Discussion & Analysis (MD&A)
• Risk factors and legal proceedings
• Business developments and acquisitions
• Market trends and competitive analysis

An insurance carrier's private equity team processes 30-50 PDF statements per quarter from different fund managers. Each statement contains similar information but in slightly different formats, requiring manual data entry into spreadsheets and PowerPoint presentations for reporting and valuation purposes.

The Challenge

• 40-60 coinvestments requiring quarterly processing
• 20-30 page statements per fund manager
• Manual data extraction consuming 20-40% of team time
• Inconsistent formats across different fund managers
• Need for both quantitative and qualitative data extraction
• Integration with existing systems (Tamale RMS, Chronograph, SharePoint)

Document Processing

DocRouter.AI would process quarterly financial statements, capital statements, and portfolio reviews from multiple fund managers, extracting structured data for Excel and PowerPoint reporting.

Key Data Extraction

• Financial metrics and performance data
• Portfolio company valuations and metrics
• Capital account information
• Qualitative insights and commentary
• Quarter-over-quarter changes and trends

Integration Benefits

• Automated extraction from Tamale RMS documents
• Direct output to Excel and PowerPoint formats
• Consistent data structure across all fund managers
• Reduced manual processing time by 80-90%
• Improved accuracy and compliance reporting

A specialty insurance wholesaler company processes handwritten and typed insurance applications submitted via email by producers. These applications contain critical customer information that must be accurately extracted and transferred to their agency management system (AMS) for policy processing and customer identification.

The Challenge

• 50% of submissions contain handwritten information
• Applications arrive via email with attachments
• Manual data entry into Ellis AMS system
• Need to identify existing customers to avoid duplicates
• Requires human review for accuracy and compliance
• Integration with existing document management systems

Document Processing

DocRouter.AI would processes insurance applications using advanced OCR for handwritten content and language models for data extraction. The system would flag low-confidence fields for human review before transferring data to the AMS.

Key Data Extraction

• Customer identification and contact information
• Policy details and coverage requirements
• Risk assessment data and checkboxes
• Handwritten notes and special instructions
• Producer and agency information

Workflow Integration

• Email integration for automated application ingestion
• Confidence-based flagging for human review
• Direct API integration with Ellis AMS system
• Temporary data storage with automatic deletion
• Automated email acknowledgments to producers
• Document classification and storage in existing systems