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PDCA stands for Plan, Do, Check, and Act, which is a cyclical methodology for process improvement.

1. Plan

• Analyze the current situation and identify problems
• Set improvement goals
• Establish specific implementation plans
• Define expected results and evaluation methods

2. Do

• Actually implement the planned content
• Collect and record data
• Monitor whether everything is proceeding according to plan

3. Check

• Analyze implementation results
• Verify goal achievement
• Identify differences from the plan
• Discover unexpected problems

4. Act

• Derive improvements based on analysis results
• Standardize and establish successful changes
• Develop countermeasures for inadequate areas
• Prepare for the next PDCA cycle

Prepare for the next PDCA cycle,
-Derive improvements based on analysis results
-Standardize and establish successful changes
-Develop countermeasures for inadequate areas

The PDCA cycle is characterized by achieving gradual improvement through continuous repetition. This methodology is used in various fields such as quality control, project management, and business process improvement. It is particularly practical in that it can start from small-scale attempts and gradually expand.

특허받은 AI 에이전트 오케스트레이션 기술
SKYNET PDCA는 전통적인 PDCA 방법론을 혁신적인 AI 에이전트 시스템에 적용한 특허 기술입니다. 이 기술은 복수의 전문화된 AI 에이전트들과 다양한 LLM(Large Language Model)들을 유기적으로 연결하여, 복잡한 문제 해결을 위한 지능형 협업 시스템을 구현합니다.

Patented AI Agent Orchestration Technology

SKYNET PDCA is a patented technology that applies the traditional PDCA methodology to an innovative AI agent system. This technology creates an intelligent collaboration system by organically connecting multiple specialized AI agents and various Large Language Models (LLMs) to solve complex problems.

Core Technical Components

1. Multi-AI Agent System
   • Deployment of specialized AI agents for each domain
   • Efficient collaboration and information exchange between agents
   • Domain-optimized problem-solving capabilities
2. Specialized LLM Network
   • Utilization of optimized LLM models for each field
   • Domain-specific reasoning and analysis
   • High-performance computing through distributed processing
3. Supervisor LLM
   • Coordination and management of overall process
   • Task prioritization and resource allocation
   • Result integration and quality control

PDCA-Based Circular Process

1. Planning Phase
   • In-depth analysis of user queries
   • Solution strategy development
   • Subtask definition and allocation
2. Do Phase
   • Task execution by specialized agents
   • Real-time data collection and analysis
   • Generation and sharing of intermediate results
3. Check Phase
   • Verification of result accuracy and consistency
   • Quality metrics evaluation
   • Identification of improvement areas
4. Act Phase
   • Process optimization based on feedback
   • Agent performance enhancement
   • Preparation for new cycle

Technical Advantages

• Automated task decomposition and allocation
• Real-time LLMs collaboration and coordination
• Continuous performance improvement
• High scalability and flexibility
• Accurate and reliable results delivery
• Remove Hallucinations and Reasoning Factcheck
• Cloud based or On-Premised