Patent Creator: An AI-Powered Intelligent Workbench for Generating Patent Disclosure Documents

Patent Creator is an AI Agent workbench centered on the core concept of 'technical core first, benchmark-driven'. It aims to help R&D personnel and patent agents efficiently generate high-quality patent disclosure documents, solving problems in traditional patent drafting such as the gap in technical understanding, low efficiency, inconsistent quality, and high costs. The project is maintained by HappyThis, with source code hosted on GitHub (link: https://github.com/HappyThis/patent_creator), and the update date is 2026-06-15.

In the traditional patent application process, inventors need to spend a lot of time organizing technical ideas, searching for existing technologies, and describing technical solutions, while patent agents need to convert technical language into legally compliant text. This process has the following problems:

• Gap in technical understanding: Inventors struggle to accurately express details in patent language, and agents may misunderstand the essence of the technology
• Low efficiency: A complete patent application requires weeks or even months of repeated communication
• Inconsistent quality: Large style differences among different agents affect the scope of patent protection and authorization probability
• High cost: Agency fees are a significant expense for startups and individual inventors

Core Design Concepts

1. Technical core first: Starting from the structured technical core, guide users to clarify technical problems, core elements of the solution, and quantitative indicators of effects to improve the accuracy of AI generation.
2. Benchmark-driven: Integrate automated benchmark execution, comparative data visualization, and existing technology benchmarking to provide key evidence for innovation and practicality.

System Architecture

Adopt multi-agent collaboration:

• Technical Understanding Agent: Extract core technical elements through structured questionnaires
• Retrieval and Analysis Agent: Automatically retrieve existing patent documents to generate analysis reports
• Claim Generation Agent: Generate independent/dependent claims and optimize language
• Specification Drafting Agent: Generate complete specifications, focusing on full disclosure and claim support
• Quality Evaluation Agent: Multi-dimensional review (legal compliance, technical consistency, creativity prediction, readability)

R&D Personnel

• Reduce communication costs: Structured output reduces repeated communication with agents
• Protect innovative achievements: Accurately and completely record technical details
• Learn patent thinking: System guidance helps master drafting methods

Patent Agents

• Improve efficiency: Automatically generate first drafts to save basic drafting time
• Quality assurance: AI-assisted checks reduce omissions and errors
• Knowledge expansion: Cross-domain technical analysis helps quickly enter new fields

Corporate IP Departments

• Standardized processes: Establish unified drafting quality standards
• Cost control: Reduce outsourcing costs and increase the proportion of internal processing
• Asset management: Structured data facilitates patent portfolio analysis

• Domain adaptation: Supports multiple fields such as mechanical engineering and AI algorithms, achieving professional output through domain-specific prompt engineering and knowledge bases
• Human-machine collaboration cycle: Key decisions (e.g., scope of claims) are controlled by humans, while AI is responsible for execution and optimization
• Continuous learning mechanism: Learn from authorized patents and examination opinions to optimize generation strategies

Current Limitations

• Complex technical solutions: The ability to understand and express multi-domain cross-cutting and highly abstract solutions needs to be improved
• Legal judgment: Creativity judgment and infringement analysis need to be led by human experts
• Multilingual support: Mainly supports Chinese; English and other languages are under development

Improvement Directions

• Introduce multi-modal capabilities to support automatic generation and optimization of attached drawings
• Deepen integration with patent office examination data to provide accurate authorization predictions
• Build a patent value evaluation model to optimize application strategies

Patent Creator represents an important application direction of AI in the legal technology field. It does not replace patent agents but becomes their intelligent assistant, transforming patent drafting from heavy manual labor to higher-level value creation. With technological progress, AI applications in the intellectual property field will become more in-depth, providing better protection tools for innovators.