About LLMWhisperer
LLMWhisperer is an AI document extraction technology that transforms complex, unstructured documents into formats that language models can understand and process accurately. It bridges the gap between document complexity and AI comprehension, enabling intelligent data extraction from PDFs, images, and other document types.
Saysimple customers use LLMWhisperer to automatically extract and understand documents shared by customers via WhatsApp—invoices, contracts, medical records, or forms—without manual data entry. Your team can instantly access key information in the shared inbox, enable smarter automations and chatbot responses, and resolve customer issues faster while maintaining document accuracy and compliance.
Populaire toepassingen
Invoice and Payment Queries in Retail
When customers share invoices or receipts via WhatsApp, LLMWhisperer automatically extracts order numbers, amounts, and dates. Your agents see pre-populated details in the shared inbox, enabling instant payment status updates or refund processing without asking customers to repeat information.
Healthcare: Patient Document Intake
Patients submit insurance forms, medical histories, or consent documents through WhatsApp. LLMWhisperer extracts relevant fields automatically, populating your CRM and triggering automations for appointment scheduling or follow-up communications—reducing administrative overhead and improving patient onboarding speed.
Real Estate: Property Document Management
Agents receive lease agreements, property photos, or inspection reports from clients via WhatsApp. LLMWhisperer extracts property details and key terms, enabling your team to quickly respond to inquiries, flag urgent issues, and maintain organized records without switching between tools.
Logistics: Shipment and Delivery Proof
Customers share shipping labels, delivery confirmations, or customs documents through WhatsApp. LLMWhisperer extracts tracking numbers and delivery status, allowing your agents to provide instant updates and resolve disputes efficiently within the shared inbox.
