Market Context — Why This Technology, Why Now

Businesses worldwide face increasing pressure to optimize operational efficiency and reduce reliance on specialized human expertise. The drive for data-driven decision-making, coupled with a shrinking skilled workforce, makes automating complex, subjective processes critical. This technology enables organizations to meet these demands by ensuring consistent, high-quality decisions, thereby mitigating risks associated with human variability and accelerating digital transformation initiatives across industries.

Key Competitive Advantages
01

Eliminates Human Dependency, Ensures Decision Consistency: Automates complex decision processes, reducing human error by up to ~66% and standardizing decision quality. Enables stable operations without reliance on skilled personnel.

02

Automates and Streamlines Business Processes: Integrates decision processing into systems, eliminating operational interruptions and reducing human decision-making effort by up to ~50%. Enables batch processing for significantly improved efficiency.

03

Establishes Market Leadership Through High Uniqueness: Demonstrates high uniqueness with only one prior art document cited by the examiner. Early adopters could establish a unique market position.

Market Opportunity
🏭 Manufacturing Industry
$150M–$250M globally (AI est.)
Automating complex decisions in quality inspection and production planning directly reduces defect rates and improves production efficiency, making it central to DX initiatives.
Industrial automation solution providers Large-scale manufacturers Quality control system developers
💰 Financial Services Industry
$150M–$200M globally (AI est.)
Accelerating and improving the accuracy of diverse decision-making tasks such as loan approvals, risk assessments, and fraud detection, enhancing competitiveness and compliance.
Fintech solution providers Retail banking institutions Insurance underwriters
💻 Service Industry
$100M–$150M globally (AI est.)
Automating optimal decisions for complex customer scenarios, such as inquiry handling and personalized service proposals, improves customer satisfaction and reduces operational workload.
Customer service platform developers E-commerce and retail companies Hospitality and travel groups
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

The patent was granted after overcoming multiple office actions with precise amendments and arguments, indicating a thoroughly examined and robust scope of rights. This strong foundation allows licensees to confidently pursue business development.

Competitive White Space

This patent primarily protects the logic and data structures for automating pre-defined decision processes. It does not cover advanced machine learning models for *learning* decision rules from data, nor specific IoT or sensor technologies for data acquisition.

Economic Impact
~$150K/year estimated cost savings per facility (est.).
estimated ROI · USD · AI analysis
ROI Calculation Logic

Assuming 5 employees spend 100 hours/month on complex decision tasks, with a monthly salary of ~$3,350/person (AI est.). A 20% reduction in decision effort through this technology could yield ~$40K/year (AI est.) in direct labor cost savings. Considering rework, opportunity loss, and delay costs from decision errors and interruptions, the total economic impact could be several times higher.

Speed to Market
4× faster than in-house development
The patent claims and detailed description clearly define the decision logic and data structure, indicating the algorithm is established. This significantly shortens R&D compared to developing a similar system from scratch. Concrete design guidelines for integration into existing business systems are provided, enabling rapid prototyping and transition to production.
Competitive Positioning

X: Decision Automation Level
Y: Operational Efficiency Improvement

Business Models & Applications
☁️ SaaS-Based Decision Engine
Companies can leverage this technology's decision logic via a cloud-based service, integrating with existing systems through APIs for rapid business automation. This minimizes initial investment and optimizes operational costs.
🔑 Technology Licensing Model
Provides a technical license for this patent to companies aiming for in-house development and operation. Licensees can combine it with their strengths to create unique value and market offerings.
🎯 Industry-Specific Solution Development
Develops customized, packaged solutions tailored for complex decision tasks in specific industries. This approach, combined with deep industry knowledge, is expected to generate higher added value.
Adjacent Application Opportunities
👵 Elderly Care & Monitoring
Elderly Care Anomaly Detection & Decision System
Applicable to systems that collect multiple decision criteria from sensor and biometric data to automatically identify abnormal behavior or health changes in the elderly. This could facilitate early intervention, reducing caregiver burden and enhancing recipient safety.
🏥 Medical Diagnostic Support
Integrated Medical Data Diagnostic Assistance
Transferable to systems that support physician diagnoses by using multiple test results (e.g., images, blood tests, questionnaires) as decision criteria. For complex cases, it could contribute to reducing misdiagnosis risks through consistent decision logic.
🚚 Logistics Optimization
Automated Optimal Logistics Route Planning
Can be utilized in systems that analyze multiple decision criteria in real-time, such as delivery costs, time, load factor, and traffic conditions, to automatically determine optimal delivery routes and vehicle allocation. This could achieve logistics cost reduction and efficient delivery planning.
Integration Roadmap — Estimated 13-Month Deployment
Phase 1: Requirements Definition & PoC
Duration: 3 months
Detailed analysis of existing decision processes to define scope and verify technology effectiveness. Define necessary decision criteria and outcomes, and design table structures.
Phase 2: Prototype Development & Testing
Duration: 6 months
Develop a prototype system implementing the core logic based on defined requirements. Conduct iterative testing with real data to optimize decision accuracy.
Phase 3: Production Deployment & Optimization
Duration: 4 months
Based on prototype validation, proceed with system deployment into the production environment. Continuously improve decision logic and optimize performance using operational data post-deployment.
Technical Feasibility
This technology centers on building a 'table' that links combinations of decision basis information with decision result information, and 'processing' to generate and search these combinations. This is primarily realized through software logic and data structures, making it relatively easy to integrate as a functional module into existing information systems. It is highly technically feasible for deployment, resembling a software update without requiring extensive hardware changes or specialized sensor integration.
Success Scenario
Implementing this technology could reduce the processing time for complex, human-dependent decision tasks by an estimated ~25%. This could alleviate workload for personnel, allowing resources to be reallocated to more strategic activities. Furthermore, decision errors could be reduced by an estimated ~15% annually, improving overall operational quality and efficiency.
Patent Record
APPLICATION NO.
特願2020-201350
REGISTRATION NO.
7124259
FILING DATE
2020/11/17
GRANT DATE
2022/08/16
EXPIRATION DATE
2040/11/17
PATENT HOLDER
株式会社ＰＬＭレボリューション
Examination History
2020年11月17日
出願審査請求書
2020年11月17日
早期審査に関する事情説明書
2021年03月18日
早期審査に関する報告書
2021年05月11日
拒絶理由通知書
2021年08月16日
意見書
2021年08月16日
手続補正書（自発・内容）
2021年09月07日
手続補正指令書（中間書類）
2021年09月13日
手続補正書（自発・内容）
2021年12月14日
拒絶理由通知書
2022年03月15日
手続補正指令書（中間書類）
2022年03月25日
手続補正書（自発・内容）
2022年04月01日
意見書
2022年04月01日
手続補正書（自発・内容）
2022年07月19日
特許査定