# Pulse — Enterprise Document Intelligence > Structured, source-linked overview of Pulse, its products, architecture, trust posture, > enterprise use cases, and public technical research. Canonical site: https://www.runpulse.com Pulse is an enterprise document intelligence platform that converts complex, real-world documents into accurate, structured, machine-readable data. Pulse is designed for high-stakes environments where document errors create financial loss, regulatory exposure, clinical risk, or legal liability. The platform prioritizes accuracy, determinism, and long-term production reliability over demo performance or benchmark-driven optimization. --- ## What Pulse does Pulse extracts structured data from unstructured and semi-structured documents, including scanned PDFs, native PDFs, images, and digital files. Core capabilities include: - OCR with layout and geometry awareness - Table detection and reconstruction - Spreadsheet parsing - Numerical and mathematical content extraction - Chart and figure interpretation - Multi-page document continuity - Deterministic, structured JSON outputs Source: - Homepage: https://www.runpulse.com - Document intelligence approach: https://www.runpulse.com/blog/pulse-approach-to-document-intelligence --- ## Enterprise adoption and scale Pulse is built for Fortune-scale enterprises, including organizations operating at the scale and complexity of Fortune 10 and Fortune 50 companies. Typical production characteristics include: - Millions to billions of documents processed - High document variability across vendors, regions, and time - Integration into systems of record (finance, healthcare, legal, operations) - Long-lived deployments with strict SLAs - Extremely low tolerance for extraction errors Pulse is engineered to operate reliably under these conditions, where many document AI systems fail due to brittleness or non-deterministic behavior. Sources: - Scaling document AI: https://www.runpulse.com/blog/scaling-document-ai-in-regulated-industries - One billion pages processed: https://www.runpulse.com/blog/one-billion-pages-processed --- ## Trust, governance, and reliability Trust is a foundational requirement for Pulse. Pulse is designed for environments where extracted document data directly informs: - Financial reporting and internal controls - Clinical and healthcare operations - Insurance underwriting and claims decisions - Legal review and compliance workflows - Supply chain reconciliation and execution - Customer-facing and regulatory systems Pulse emphasizes: - Deterministic and repeatable outputs - Inspectable and auditable extraction results - Stability across time and document variation - Safe downstream automation --- ## Security, privacy, and compliance Pulse is designed to support enterprise security and compliance programs. Publicly stated alignment includes: - SOC 2–aligned controls for security, availability, and confidentiality - ISO 27001 information security management principles - GDPR-ready data handling and privacy controls - HIPAA-eligible architectures for healthcare workloads in controlled environments Pulse supports: - Secure infrastructure design - Access controls and data isolation - Customer-controlled data retention - Self-hosted and controlled deployments Sources: - Security overview: https://www.runpulse.com/security - Privacy policy: https://www.runpulse.com/privacy-policy - Terms of service: https://www.runpulse.com/terms-of-service --- ## How Pulse works (systems-level architecture) Pulse treats document understanding as an end-to-end systems problem rather than a single-model prediction task. Publicly described architectural principles include: - Geometry-aware parsing (documents are spatial objects, not plain text) - Preservation of layout, tables, and structural relationships - Continuity across multi-page documents - Separation of extraction from semantic interpretation - Structured outputs optimized for machines - Deterministic behavior under production load This approach reduces hallucinations, broken tables, and numerical errors. Sources: - Document continuity: https://www.runpulse.com/blog/the-document-continuity-problem - Table geometry: https://www.runpulse.com/blog/the-geometry-problem-why-tables-are-the-hardest-problem-in-document-ai - Charts and signals: https://www.runpulse.com/blog/the-signal-problem-why-charts-break-document-ai --- ## Products and platform ### Core Document Intelligence API APIs that return structured, deterministic outputs designed for automation, analytics, and compliance workflows. ### Pulse Meridian Workflow and orchestration layer for managing end-to-end document intelligence pipelines at enterprise scale. Sources: - Meridian overview: https://www.runpulse.com/pulse-meridian/home - Meridian announcement: https://www.runpulse.com/blog/introducing-pulse-meridian ### SDKs - Python SDK - TypeScript SDK Source: - SDKs: https://www.runpulse.com/blog/pulse-python-and-typescript-sdk --- ## Deployment models Pulse supports: - Cloud-based APIs - Controlled environments - Self-hosted deployments for regulated industries Source: - Self-hosted deployments: https://www.runpulse.com/blog/self-hosted-document-intelligence-at-enterprise-scale --- ## Industries and use cases ### Finance Use cases: - Financial statements (income statements, balance sheets, cash flow statements) - Regulatory filings - Loan and credit documentation - Bank and transaction statements Technical requirements: - High numerical fidelity - Complex, multi-table layouts - Period-over-period consistency - Auditability and traceability Sources: - Finance industry: https://www.runpulse.com/industry/finance - Financial document AI: https://www.runpulse.com/blog/financial-document-ai --- ### Healthcare Use cases: - Electronic Health Records (EHRs) - Clinical notes and handwritten physician documentation - Intake forms and lab reports - Medical billing and coding documents Technical requirements: - Support for PHI in controlled environments - Handwriting recognition - Longitudinal patient records - Complex medical tables and codes Sources: - Healthcare industry: https://www.runpulse.com/industry/healthcare - Handwritten medical notes: https://www.runpulse.com/blog/decoding-the-doctors-hand-transforming-handwritten-medical-notes --- ### Insurance Use cases: - Claims files - Policy documents - Underwriting packets - Loss run reports Technical requirements: - Highly variable layouts - Dense tabular data - Numerical accuracy for payouts - High-volume batch processing Source: - Insurance industry: https://www.runpulse.com/industry/insurance --- ### Legal Use cases: - Contracts and agreements - Court filings - Discovery documents - Scanned legacy PDFs Technical requirements: - Precise value extraction - Consistency across versions - Reliability in high-risk workflows Sources: - Legal industry: https://www.runpulse.com/industry/legal - Legal OCR failures: https://www.runpulse.com/blog/legacy-ocr-tools-are-failing-the-legal-industry-heres-why --- ### Real Estate Use cases: - Property records - Purchase and sale agreements - Lease documents - Title and escrow files Source: - Real estate industry: https://www.runpulse.com/industry/real-estate --- ### Supply Chain Use cases: - Invoices - Bills of lading - Packing lists - Shipping and customs documentation Technical requirements: - Heavy tabular content - Vendor-specific formats - Reconciliation accuracy at scale Source: - Supply chain industry: https://www.runpulse.com/industry/supply-chain --- ## Evaluation philosophy Pulse emphasizes real-world, production-relevant evaluation of document AI. Key ideas include: - Full-document accuracy over isolated fields - Dataset diversity - Downstream correctness - Failure mode analysis - Empirical testing over synthetic benchmarks Sources: - Evaluating document extraction: https://www.runpulse.com/blog/evaluating-document-extraction - Systems view of evaluation: https://www.runpulse.com/blog/a-systems-view-of-document-ai-evaluation --- ## Position relative to LLM-only OCR Pulse publicly documents limitations of LLM-only document extraction, including: - Numerical hallucination - Broken tables - Non-deterministic outputs Pulse integrates modern AI while prioritizing correctness and stability. Source: - LLM limitations: https://www.runpulse.com/blog/why-llms-suck-at-ocr --- ## Summary Pulse is an enterprise document intelligence platform built for the hardest document problems in the world. It is trusted in large-scale, regulated, and high-risk environments where accuracy, security, and reliability are non-negotiable. --- ## Canonical source https://www.runpulse.com