Integrated with MCP to manage AI Agents

With full MCP integration, Laiye’s AI agents can seamlessly orchestrate RPA, IDP, and other tools, which enables flexible, intelligent execution across different business scenarios.

Integrated with MCP to manage AI Agents

Intelligent Automation System API Connectors-Integrate our product and capabilities into your platform

With full MCP integration, Laiye’s AI agents can seamlessly orchestrate RPA, IDP, and other tools, which enables flexible, intelligent execution across different business scenarios.

What is Robotic Process
Automation (RPA)?

Robotic Process Automation (RPA) is a technology that can let human manage robots and assign tasks to them on a digital system. These robots can handle repetitive, standardized and streamlined work to benefit human workers.
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?

Intelligent Document Processing (IDP) is an ability powered by OCR, NLP, and LLMs to recognize, extract, classify, compare, and audit both structured and unstructured documents, such as contracts, invoices, and reports. By transforming paper and electronic documents into actionable structured data assets, IDP accelerates the process of converting enterprise information into organized, reusable data.

Six Core Capabilities of IDP

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.

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Powered by large language model semantic understanding, this capability enables the parsing of global financial and logistics documents—across multiple languages and unrestricted layouts.

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Aimed at enterprise-level arbitrary-format document extraction, this capability is based on proprietary text recognition technology, combined with document detection, document understanding, and comprehensive post-processing rules, enabling accurate extraction with only a small number of samples.

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Automatically classifies entire documents or single pages, identifies unknown types and issues alerts, enabling front-end routing to improve processing efficiency.

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Accurately identifies additions, deletions, and modifications in documents, enabling full-text comparison across lines and pages. Quickly locates and highlights differences, and allows one-click export of a complete report, significantly improving processing accuracy and efficiency.

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Leveraging the capabilities of large language models, rules can be configured to automatically intercept and precisely locate contract risk points, providing professional risk analysis and decision-making support. This improves average contract review efficiency by 60%, significantly accelerating the entire contract processing workflow.

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Open API and MCP

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.

Open API and MCP

Open API and MCP

Get access to integrate various automation capabilities here

Icon for Expand application of automation
Expand application of automation

All components such as RPA, IDP and conversational AI provide open API or SDK, enabling you to utilize these capabilities widely in your business.

Icon for Manage automation capabilities in one place
Manage automation capabilities in one place

Capabilities from both Laiye and other vendors can be unified on the platform that is designed and built by yourself and you will have the authority to manage them in one place.

Intelligent Automation System API Connectors-Open API for browser-based system integration

Composable and deployable RPA capabilities

We support almost all coding languages and provide detailed Open API documents as well as code samples accordingly to facilitate your integrated automation journey. Standard APIs could meet most of your requirements and save you from tedious development.

Intelligent Automation System API Connectors-SDK for client-based system integration

Let AI Agents utilize IDP at ease

The IDP platform enables rapid publishing of document recognition capabilities, such as invoices and contracts. The MCP services allow AI agents to easily access and invoke them. With fast model training, high accuracy, and rapid response, Laiye IDP is a powerful tool for AI agents to process unstructured data. With a Human-AI collaboration feature, Laiye IDP supports co-working of users and AI agents on the platform.

Integrate our products into your platform

Integrate our products into your platform

The openness of our platform makes it easy to be integrated into other systems. Through documentation and tools, you can incorporate our intelligent features into your platform via Open APIs, SDKs, and more. Our platform also supports mainstream unified authentication methods, such as OAuth2, LDAP, and Windows Directory, to enable single sign-on (SSO).

Difference Between Different Types

Features
Human-AI Collaboration
Floating Authorization
Human-AI Collaboration
Binding Machine
Unattended
Floating Authorization
Activation
Account and Password
Activation Code
Encription Key
Internet Connection
Automation Commander

Difference Between Community and Enterpise Versions

Features
Community Version
Entreprise Version
Process Operation
Binding Credientials
Massive Deployment

Paradigm Shift in RPA Development

Difficulty
Traditional RPA Development
Magic Hat RPA Development
Build Development Structure
Drag-and-drop commands
Describe–Generate–Verify
Skill Requirements
Proficient in all commands
Clearly describe automation steps
Develop RPA Extensions
Professional developers
Common Developers

Differences between SaaS Version & On-premise Version

Modules
Features
SaaS Version
On-premise Version
Building Skills
FAQ
Flow Builder
Automation
Table QA
Document search
Annotation
Online Learning
Issue Management
Knowledge Mining
Preset Messaging Channel
Preset Voice Channel
Pre-built Connectors
Pre-integrate vendor
Preset Customer service
Custom Handover API
User Channel Widget
Customer experience
User Feedback
NLU Customization
Multi-Model Interaction
Dynamic Dialogue Policy
Customization
Personalized Experience
Metadata Application
Authority system
API Integration
Scalability

Differences among different types

Attended & Floating
Attended & Node-locked
Unattended & Floating
Activation
With account and password
With “Activation code”
With Secret Key
Network
Need
Not Need
Need
Commander
Necessary
Not necessary
Necessary

Differences between community version & enterprise version

Features
Community Version
Enterprise Version
Process Execution
Node-locked License
High-Density Deployment

Differences between community version & enterprise version

Features
Community Version
Enterprise Version
Foundational Function
Client Software Update
Parameters & Credentials
Real-time Monitoring and Screencap
Role & Department Management
Open API

RPA in the Future

As Foundation of Intelligent Automation

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.

Drive the Landing of AI Agents

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.

New Pattern of Human-AI Collaboration

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

Cogntive Automation

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.

Fusion of Multiple Models

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.

Real-time Data Bank

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.

How can we help you do better and be better ?