Handle paper documents and build data asset
Laiye IDP supports recognition across multiple languages, formats, and complex layouts, enabling fast and accurate digitization of diverse documents.
Handle paper documents and build data asset
Laiye IDP supports recognition across multiple languages, formats, and complex layouts, enabling fast and accurate digitization of diverse documents.
Handle paper documents and build data asset
Laiye IDP supports recognition across multiple languages, formats, and complex layouts, enabling fast and accurate digitization of diverse documents.
What is robotic process automation (RPA)?
The evolution of AI, especially large language model (LLMs) significantly influnces the development of RPA. Besides serving the as the executing role, AI can offer the orchestration, governance, and security assurance for deployment of enterprise-grade intelligent automation.
What is intelligent document processing (IDP)?
Six Core Capabilities of IDP
Core advantages
Leading performance
Powered by dual engines, semantic understanding via LLMs and Laiye’s proprietary OCR, our solution delivers top-tier recognition accuracy, even in complex scenarios.
Enterprise-grade securityCertified by international standards such as ISO/IEC 27001, ensuring 99.9% system reliability and data security.
Agile and intelligent
Zero-shot document processing, with closed-loop collaboration across departments. Human feedback fuels continuous self-learning and iteration.
Open and integrated
Natively integrated with RPA. Seamless API/MCP connectivity with 50+ business systems and AI applications for end-to-end intelligent document handling.
General Recognition
Text Recognition: Accurately extracts text (with positional information) across diverse scenarios, supporting multiple languages such as Chinese, English, Spanish, and French. Handles complex conditions including occlusion, skewed angles, and densely packed text.
Applied Scenarios
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Extract key information (order numbers, addresses, chat content, etc.) from screenshots or social media images to facilitate customer service with faster responds.
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Convert medical records, invoices, and legal files into searchable, structured data with OCR and spatial analysis, integrating seamlessly with ERP/HRP/DMS systems.
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Auto-detect sensitive content in promotional materials, live captions, or UGC to flag violations. This reduces risks in scenarios like ad review and public opinion monitoring.
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Instantly translate and archive text from foreign documents, posters, or manuals with OCR or other translation tools, to improve global team communication and information sharing.
Difference between types
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Difference between community and enterpise versions
Paradigm Shift in RPA Development
Multilingual coverage
Supports printed text recognition in 50+ languages, including Chinese, English, French, Spanish, Japanese, Korean, Russian, and Portuguese. Compatible with formats like JPEG, JPG, PNG, PDF, BMP, and TIFF to boost processing efficiency.
Optimized for complex scenarios
Specifically enhanced to handle challenging conditions such as rotated, occluded, skewed text, dense content, complex backgrounds, uneven lighting, motion blur, and handwritten input.
High accuracy
Laiye IDP leverages proprietary machine learning to automatically detect and recognize text in images, achieving over 97% accuracy across different scenarios.
Differences between SaaS Version & On-premise Version
Differences among different types
Differences between community & enterprise versions
Differences between community version & enterprise version
RPA in the future
RPA will continue to be a core tool in enterprise digital transformation. By leveraging low-code platforms, it lowers the development barrier and enables cross-system task automation. Its non-intrusive nature allows for seamless integration with legacy systems, ensuring execution of complex workflows. Meanwhile, containerization drives its evolution toward cloud-native architecture, enhancing collaboration with API-based automation.
Digital Worker Builder: Enables graphical configuration of AI Agents with complex decision-making capabilities to support advanced automation scenarios.
Agent Interaction Hub: Integrates MCP technology to provide standardized system interfaces, allowing business users to directly trigger automation processes.
Cognitive Automation Upgrade: Combines large language models to enable natural language interaction, document comprehension, and intelligent decision-making.
Employee Empowerment: Frees human resources from repetitive tasks (e.g., monthly report preparation in finance accelerated by 40x), allowing focus on higher-value work.
Human-AI Collaboration: Enables natural language interaction through chatbots and smart forms, automatically triggering manual intervention when exceptions (like invoice issues) arise.
Democratized Automation Skills: Empowers business users to build automation workflows independently, with a low-code approach validated by an 800,000-strong developer community.
RPA center of excellence
The RPA center of excellence (CoE) is a cross-functional team that consolidates best practices in RPA deployment, standardizes data interfaces and operation models, and drives enterprise-wide automation at scale.
For the enterprise: Enhances operational decision-making, unlocks data value, and reduces the cost of repetitive tasks.
For employees: Empowers staff to develop RPA skills, boosting productivity and creativity.
IDP in the future
Driven by large language models, semantic understanding of documents evolves toward decision-making analysis, enabling a closed-loop decision cycle, from clause impact analysis, cost simulation, to actionable recommendations.
Enables joint analysis of text, images, and tables to generate actionable business insights. Breaking the limitations of single-modal processing, it builds an integrated analysis pipeline, from documents to seals, signatures, and data tables.
Connects with enterprise data asset management platforms to accelerate the structuring of data resources (“into the table”). Builds a value chain from document data, to asset valuation, and to business insights.