Document intelligence for trust and scale.Pulse uses OCR, layout, and vision models to produce high quality outputs from complex documents for enterprise and AI-native teams.
Pulse is an AI-powered document intelligence platform that enables enterprises and AI-native applications to extract, structure, and process information from complex, unstructured documents with production-grade accuracy. Using advanced OCR, computer vision, layout analysis, and specialized vision-language models, Pulse transforms PDFs, scanned documents, spreadsheets, presentations, images, and other enterprise file formats into structured, machine-readable data suitable for business automation and AI workflows. The platform is designed to handle challenging document layouts, including tables, charts, handwriting, multi-column formats, and forms, while maintaining high accuracy at enterprise scale.
Pulse provides a unified platform for document extraction, schema-based data parsing, document segmentation, and API-driven automation. Developers can build custom extraction pipelines through a visual interface or integrate directly using Python, TypeScript, and REST APIs. The platform also supports structured JSON extraction, table-to-Excel conversion, asynchronous processing, and reusable pipeline templates for production deployments.
Built for highly regulated industries such as financial services, healthcare, insurance, legal, and real estate, Pulse offers enterprise-grade security with SOC 2 Type II, ISO 27001, GDPR, and HIPAA compliance, along with cloud, private VPC, and on-premises deployment options. Having processed over one billion pages, Pulse helps organizations automate document-intensive workflows, improve data quality, and accelerate AI-driven business processes while reducing manual effort.
Highlights
AI-powered document intelligence and data extraction platform
Advanced OCR, computer vision, and layout-aware document processing
Extracts structured data from PDFs, images, spreadsheets, and presentations
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Pulse uses a single usage-based dimension. You buy credits, and each page you process consumes credits. Processing covers OCR, layout detection, and extraction. Your cost scales directly with how many pages you run through the service. There are no separate tiers or instance sizes to choose from. The more pages you process, the more credits you use. This keeps billing tied to actual document volume rather than a fixed subscription.
Top-of-mind questions for buyers
What counts as one page for credit consumption?
A page is one page of a processed document. Pulse handles PDFs, spreadsheets, presentations, images, and Word files. Each page runs through OCR, layout detection, and extraction, which together consume credits. Multi-page documents consume credits per page, so a 10-page file draws more credits than a single-page file.
Does credit consumption change based on document complexity or workflow steps?
Credits are consumed per page for OCR, layout detection, and extraction. The workflow includes optional steps like classification, schema extraction, table reconstruction, and splitting. Classification is described as a lower-cost step that routes documents before extraction. More processing steps applied per page can raise the credits each page draws.
Do stored or reprocessed documents consume additional credits?
Credits are consumed when a page is processed. Reprocessing the same document runs it again and consumes credits again. Pulse suggests caching to avoid reprocessing. Processed data is deleted automatically after 48 hours, so storage itself does not appear to drive ongoing credit use.
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