Extracts structured key-value pairs from arbitrary, noisy, or unstructured text using LLMs and provides output in multiple formats (JSON, YAML, TOML) with type safety.
Enables intelligent document processing by extracting text, classifying document types, and generating structured summaries from PDFs and images using vision LLMs.
Extracts structured JSON data from unstructured text using predefined schemas for receipts, invoices, resumes, and emails. It allows users to transform messy text into organized data through built-in or custom-defined fields.
Enables local analysis of unstructured documents (PDF, DOCX, PPTX, SVG, PNG) by extracting text and structure with citation anchors, and verifies summaries against source material before a human approves saving a report.
Enables fact-checking of AI responses against reliable sources and validation of responses against document content to ensure accuracy and reliability.
Enables AI agents to extract structured data from PDFs with confidence scores and provenance, and to search, review, and correct documents via MCP tools, resources, and prompts.