LandingAI

LandingAI provides an agentic document extraction platform that converts unstructured documents—such as invoices, receipts, contracts, medical records, and forms—into structured, machine-readable data. The core offering, Agentic Document Extraction (ADE), uses AI agents to automatically parse text, tables, and layouts from scanned PDFs, images, and digital files without requiring custom training or manual template creation. Each extraction result includes a confidence score and precise page-level coordinates, enabling developers to verify every data point and trace it back to its original source. This audit trail ensures that downstream applications—like enterprise resource planning systems, compliance databases, or analytics pipelines—receive trustworthy, verifiable inputs. The platform is designed for high accuracy on real-world documents, handling complex layouts, nested tables, multi-page documents, and handwritten or typed text. In benchmarks, LandingAI achieves 99.16% accuracy on DocVQA-style tasks without relying on image-based OCR alone, instead combining vision-language models with structured reasoning. Developers can integrate the service through REST APIs, receiving JSON or CSV outputs that map directly to their data schemas. The system supports batch processing, real-time extraction, and incremental updates, making it suitable for both small-scale automation and enterprise-scale document workflows. Key use cases include automating accounts payable by extracting invoice line items, vendor names, and amounts; digitizing patient intake forms in healthcare; processing loan applications with mortgage statements and pay stubs; and converting legal contracts into searchable metadata. Because each extraction step is auditable, regulated industries such as finance an