Inshared, the Netherlands' pioneering online insurance company known for refunding surplus profits to customers, faced significant operational challenges with manual document processing. Processing dozens of daily emails containing invoices, insurance papers, and other attachments required extensive manual effort to link documents to internal dossiers. SevenLab implemented an intelligent AI pipeline that automatically processes emails and attachments, extracting relevant identifiers and routing documents to appropriate systems. This solution eliminated over 1 FTE worth of manual labor annually while preventing countless processing errors.

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Optimizing insurance operations through intelligent document automation

The insurance industry processes vast amounts of documentation daily, from policy applications to claims documentation. For digital-first insurers like Inshared, efficient document management directly impacts customer service quality and operational costs. SevenLab's SDAAS approach addresses these challenges through purpose-built AI solutions that integrate seamlessly with existing business processes.

The Challenge

Inshared, operating as the Netherlands' first profit-sharing insurance company since 2009, built their business model on efficiency and customer value. However, their operations faced a critical bottleneck that threatened both efficiency and accuracy.

The company received dozens of emails daily containing critical attachments including invoices, insurance documentation, policy papers, and claims materials. Each document required manual review to identify the appropriate internal dossier for storage and processing. This manual linking process consumed enormous amounts of staff time, with employees spending hours each day reviewing attachments, extracting relevant identifiers, and manually filing documents in the correct system locations.

The manual process created multiple pain points beyond time consumption. Human error rates were significant, with documents occasionally misfiled or linked to incorrect dossiers. Processing delays impacted customer service response times, particularly for time-sensitive claims and policy updates. The labor-intensive nature of the work also limited scalability, as document volume growth would require proportional staff increases.

"We recognized that our manual document processing was becoming a significant operational constraint," noted an Inshared operations manager. "As we grew, the time required for document management was taking resources away from customer-focused activities that truly drive value."

The Solution

SevenLab developed a comprehensive AI agent specifically designed to automate Inshared's document processing workflow. The solution leverages advanced natural language processing and computer vision technologies to understand document content and context.

The AI agent monitors incoming email flows in real-time, automatically identifying messages containing relevant attachments. Using sophisticated text analysis, the system reads both email content and attachment text to extract key identifiers such as policy numbers, customer references, claim identifiers, and document types.

The system accurately identifies document categories and appropriate dossier assignments even when documents vary in format or structure. The AI agent maintains high accuracy rates while processing documents at speeds impossible for human operators.

Integration with existing systems was seamlessly handled through SevenLab's SDAAS methodology. The solution connects directly with Inshared's document management infrastructure, automatically routing processed documents to correct locations while maintaining full audit trails and compliance records.

Results and Impact

• 1+ FTE annual time savings: Eliminated equivalent of full-time employee worth of manual processing

• Zero processing errors: Automated system prevents human mistakes in document classification

• Real-time processing: Documents routed instantly upon receipt, improving response times

• 100% scalability: System handles volume increases without additional staffing

• Enhanced compliance: Automated audit trails ensure complete documentation tracking

• Improved customer service: Staff resources redirected to customer-facing activities

• Cost reduction: Significant operational savings through labor automation

Future Developments

The success of the document processing automation opens opportunities for expanded AI integration across Inshared's operations. Potential developments include automated claims assessment, policy recommendation engines, and customer communication optimization.

SevenLab's SDAAS approach enables continuous improvement and feature expansion without disrupting existing operations. As Inshared's business grows, the AI systems can be enhanced with additional capabilities and expanded to cover new document types and processing requirements.