LLM-powered invoice recognition to speed up audit
Extract data from high-volume, multi-format invoices in 50+ languages, with billions of annual calls.
LLM-powered invoice recognition to speed up audit
Extract data from high-volume, multi-format invoices in 50+ languages, with billions of annual calls.
LLM-powered invoice recognition to speed up audit
Extract data from high-volume, multi-format invoices in 50+ languages, with billions of annual calls.
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 security
Certified 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.
Invoice Recognition
Powered by LLM semantic understanding, this capability enables the parsing of global financial and logistics documents across multiple languages and unrestricted layouts.
Applied Scenarios
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Automatically scan and summarize VAT invoices to generate accurate tax reports. Exhausting manual review is significantly reduced.
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Support multi-language documents, and extract crucial data such as customs declarations, certificates of origin, and letters of credit. Automatically match trade rules to reduce port delays and compliance risks.
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Quickly capture tracking numbers, goods details, and sender/receiver info from multilingual shipping and inventory forms to enable real-time logistics tracking.
Global invoice parsing
By saving employees from repetitive and mundane tasks, RPA boosts workforce satisfaction, engagement, and productivity. With its non-intrusive nature, RPA can be quickly implemented to accelerate digital transformation, especially in workflows involving legacy systems that lack APIs, database access, or rely on virtual desktop infrastructure (VDI).
Laiye RPA provides intelligent agents with a reliable toolkit. Thanks to advanced AI capabilities, RPA can now optimize resource-intensive operations, such as processing millions of documents, handling thousands of customer emails, and extracting key information from vast amounts of unstructured data.
Proven at scale
By saving employees from repetitive and mundane tasks, RPA boosts workforce satisfaction, engagement, and productivity. With its non-intrusive nature, RPA can be quickly implemented to accelerate digital transformation, especially in workflows involving legacy systems that lack APIs, database access, or rely on virtual desktop infrastructure (VDI).
Laiye RPA provides intelligent agents with a reliable toolkit. Thanks to advanced AI capabilities, RPA can now optimize resource-intensive operations, such as processing millions of documents, handling thousands of customer emails, and extracting key information from vast amounts of unstructured data.
Difference between types
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binding machine
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Difference between community and enterpise versions
Paradigm Shift in RPA Development
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.