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物流倉庫の自動化システム
Business

Reading the future, driving decisions, moving society forward

With AI agents at the core, we leverage Web3 and other technologies to provide integrated support from prediction to decision-making and value creation. We aim to build decision-making foundations resilient to supply chain changes and contribute to solving challenges across society.

Services

Our Services

Demand Forecasting AI Agent

A next-generation predictive AI agent utilizing LLM and MCP that fundamentally solves structural issues in supply chains.

High-Precision Prediction Models

Provides optimal predictions for different industries and applications by combining multiple advanced methods including DeepAR, TFT, and XGBoost.

Natural Language Interface

Realizes intuitive operation that field staff can use immediately just by 'asking questions' in natural language. Delivers 'actionable decisions' in real-time.

Existing System Integration

Seamlessly integrates with existing business systems such as ERP, WMS, and EDI, smoothly integrating into business workflows.

Challenges

Supply Chain Challenges

With rapid changes, fragmentation, and opacity overlapping, global supply chains are in chaos. Japanese companies relying on 'people and intuition' face limits in prediction and decision-making, with decision uncertainty becoming increasingly serious. We solve structural issues fundamentally, starting from prediction.

These challenges manifest in all decision-making scenarios

Target Audience: All decision-makers from field operations to management in supply chain-related companies
Challenge Scenarios: Production and logistics planning, demand forecasting, inventory adjustment meetings, sales planning, demand coordination with customers, etc.
Impact Scope: Production sites, inventory management, sales planning, supply chain management, business management, information systems departments, etc.

Human Challenges

Dependent on intuition and experience with no reproducibility. Past decisions are not learned from, leading to many repetitions.

Information Challenges

Internal and external information is not utilized for decision-making. ERP and management tools are fragmented and cannot be integrated.

Time Challenges

Internal coordination and approval take time, delaying responses. Decision rationale is unclear, making it impossible to fulfill accountability.

Quality Challenges

Vulnerable to external changes, resulting in stockouts and excess inventory. Cannot respond to instant changes such as price surges, weather, and policies.

Product

Next-Generation Predictive AI Agent 'OVERSEE'

OVERSEE is a next-generation predictive AI agent where AI learns through dialogue, predicts, and guides decisions. With a dedicated dashboard that supports demand-driven decision-making across departments and systems in an integrated manner, it realizes simple operation and smooth implementation.

Practical Application Based on LLM and MCP Emergence - Next-generation technology using the latest large language models and multi-purpose causal inference achieves functionality and accuracy that far exceed conventional prediction tools.
Design Specialized for SCM Operations - Provides more accurate predictions and recommended actions with algorithms specialized for supply chain-specific prediction challenges (demand forecasting, lead time fluctuations, etc.).
Competitive Operability and Field Adaptability - Generates 'output that can be used directly in the field' by conforming output formats to business specifications. AI does not operate independently but integrates with existing business systems.
OVERSEE Dashboard
Impact

Economic Effects of Implementation

Implementation case assuming annual sales of 100 billion yen (manufacturing/trading company model) and total inventory of 10 billion yen

$125M

Annual Total Effect

$54M

Working Capital Reduction through Inventory Optimization

$39M

Reduction of Stockout and Sales Opportunity Losses

$28M

Optimization of Procurement and Logistics Costs

$4M

Improvement in Decision Workload and Operational Efficiency

Strategy

Growth Strategy - Business Development Roadmap

Aiming to form the OVERSEE Global Ecosystem with a view to 2030

2025-2026

Establishing Product Foundation

  • Strengthening our technical capabilities, human resources foundation, and sales functions
  • Launch of predictive AI agent SaaS for large enterprises
  • Expand the number of implementing companies and case accumulation centered on high-precision models
  • Continuously implement product UI improvements
2027-2028

Market Expansion & Service Evolution

  • Pursue technological innovation in-house and ensure thorough security
  • Begin service expansion to multilingual support and global markets
  • Expand domains including overall SCM, financial forecasting, and risk management
  • Promote ecosystem formation through multi-platform deployment
2029-2030

Global Ecosystem Formation

  • Lead the industry and promote standardization across the entire industry
  • Form a 'Global AI Prediction Ecosystem' connecting companies worldwide
  • Integrated OVERSEE becomes a global business standard as prediction infrastructure

Creating the Future Together

We have a vision to move field operations starting from prediction and change the world. As a partner in creating the future of supply chains, please feel free to contact us.