Product features, releases, updates, roadmaps, and everything in between AI, automation, and data.
Modern Insurance OCR is the foundation for automating document-intensive processes like claims and underwriting. The best OCR for insurance goes beyond simple text recognition to accurately extract data from complex layouts, handwritten fields, and multilingual forms.
Unstract’s AI-powered multi-document PDF splitter API reads both text and layout to detect boundaries, then returns perfectly labeled, individual PDFs plus JSON metadata—no templates, keywords, or page numbers required
LLMWhisperer is an advanced OCR software for data entry that excels at extracting and structuring data from complex, unstructured documents like scans and handwritten forms. Unlike traditional OCR, it preserves layouts and integrates seamlessly into automated enterprise workflows, reducing manual work and improving accuracy. This makes it an ideal solution for reliable, large-scale OCR data entry in 2025.
Millions of contracts, agreements, and compliance documents are being produced by law firms each year. Most of them are unstructured,
Unstract offers automated, template-less AI document processing with custom schema support. This post highlights the inefficiencies of legacy, template-based extraction and demonstrates how Unstract’s schema-driven approach enables accurate, flexible data extraction from any document format.
Discover how integrating Unstract’s precise document extraction with Crew.AI’s agentic orchestration enables a powerful, end-to-end workflow for scalable and adaptive financial data processing.
See Unstract in action with walkthroughs of core features and real extraction workflows.
Managed cloud, on-premise, or open-source. Unstract adapts to your infrastructure needs, so choose what works best for you.
Prompt engineering Interface for Document Extraction
Make LLM-extracted data accurate and reliable
Use MCP to integrate Unstract with your existing stack
Control and trust, backed by human verification
Make LLM-extracted data accurate and reliable
