電費半分 Product Lineup

Cognitech.DEV Inc. researches and applies new AI technologies such as machine learning, deep learning, and natural language processing. This enables the resolution of real-world problems across various fields, including image recognition, autonomous driving, and natural language processing. Furthermore, through collaborative research with universities and research institutions, we incorporate advanced technologies and provide innovative solutions. 【Business Areas】 ■ Robot system design ■ AI failure cause analysis ■ AI application development ■ Simulation applications *For more details, please refer to the related links or feel free to contact us.

Cognitech.DEV, a group company of ours, is an IT solutions company established in 2024 that utilizes AI and robotics technology. Our technical staff have extensive practical experience in AI, automation, and robotics, providing support from requirement definition to PoC (Proof of Concept), implementation, and operation with a field-oriented perspective. ■ Business areas: AI, robotics, cloud, software development, data analysis ■ Strengths: Rapid implementation capability, data structuring, advanced optimization (tuning) ■ Mission: To transform the "complexity" of the field into "usable knowledge" through technology *For more details, please download the PDF or feel free to contact us.

We would like to introduce the "AI-FTA Analysis System" provided by Cognitech.DEV. This is an AI-based FTA system that identifies the causes of failures and malfunctions by combining internal data and system information with AI models to analyze complex system failures. It supports risk reduction and optimization of maintenance planning. Additionally, it can automatically extract entities from multiple failure log databases, enabling rapid identification of causes. 【Advantages】 ■ Automatic extraction of entities from multiple failure log databases allows for quick identification of causes. ■ High-precision analysis is achieved through large-scale data analysis using AI. *For more details, please download the PDF or feel free to contact us.

We would like to introduce "Private AI for Corporations" provided by Cognitech.DEV. It integrates multiple internal data sources in real-time, enabling advanced analysis and automation through AI. We provide appropriate AI solutions that include model retraining to meet various needs, maximizing support for operational efficiency. 【Features】 ■ Integrates multiple internal data sources in real-time, enabling advanced analysis and automation through AI ■ Provides appropriate AI solutions that include model retraining to meet various needs ■ Builds the environment according to the customer's security requirements *For more details, please download the PDF or feel free to contact us.

『AI-FTA Agent』は、従来のFTAをベースに、AIによる因果推論と知識活用を 組み合わせた新しい分析ツールです。 提供するのは、データの整理と知識化をはじめ、必要に応じたセンサー連係、 因果分析AIで根本解決、クラウド活用でコスト最適化、自動制御での負担軽減の 5つのサービス。 「導入の第一歩がわからない」「自社でも本当に使えるのだろうか」 そんなお悩みも、ぜひご相談ください。専門スタッフが丁寧にご案内 いたしますので、まずはお気軽に現場課題をお聞かせください。 【特長】 ■故障解析の自動化 ■因果推論による再発防止 ■現場データ連携 ※詳しくはPDFをダウンロードしていただくか、お気軽にお問い合わせください。

"Cognitech.DEV" is an AI solution that connects on-site data and judgment, leading to execution. It structures and makes reproducible the "judgment logic" from existing reports, inspection records, and trouble history. This product is chosen by companies with equipment maintenance and manufacturing sites, as well as customers whose trouble response has become dependent on specific individuals. [Features] ■ Can start from a single piece of equipment ■ Expandable to multiple themes ■ Future compatibility with MES/robot collaboration *For more details, please download the PDF or feel free to contact us.

The "AI-FTA Agent" is a field decision support tool that automatically organizes the causal relationships of failure causes, priorities to check, and supporting documents based on past failure reports, inspection records, and equipment materials. When you are unsure in the field, you can check: "Which cause should be verified first?" "What documents support that judgment?" This allows you to accumulate individual failure responses as a company asset for decision-making. 【Features】 ■ Utilize existing materials as they are Simply upload failure reports, inspection records, and equipment manuals. ■ Visualize causal relationships with a logic tree Organize the overall structure of failure causes and the flow of what to verify. ■ Support field decisions with evidence By asking questions in a chat, possible causes, inspection methods, and reference materials are provided. ■ Can start from one piece of equipment or one theme Test on a small scale and expand to multiple pieces of equipment or themes. *For more details, please refer to the PDF materials. Feel free to contact us for demo requests or trials with your own materials.

In the energy industry, equipment maintenance is essential for the stable operation of facilities. Particularly in large-scale equipment such as power plants and plants, failures leading to shutdowns can result in significant losses. It is necessary to effectively utilize past failure cases and inspection records to conduct rapid and accurate cause investigation and recovery operations. The AI-FTA Agent enables the identification of failure causes based on past materials and provides appropriate response procedures. 【Usage Scenarios】 - Maintenance of power generation equipment, substation equipment, and plant equipment - Rapid cause investigation during failures - Inheritance of know-how from veteran technicians 【Benefits of Implementation】 - Reduction in failure response time - Improvement in equipment operating rates - Support for the development of technicians

In quality control within the manufacturing industry, maintaining product quality and improving production efficiency are essential. Particularly during incidents on the production line, rapid identification of causes and appropriate responses are crucial. It is important to effectively utilize past failure data and inspection records, relying not on individual knowledge but enabling anyone to quickly identify causes and implement suitable measures. The AI-FTA Agent addresses these challenges and contributes to the efficiency of quality management. 【Usage Scenarios】 - Investigating causes during incidents on the production line - Responding to failures in the quality control department - Transferring the know-how of veteran technicians - Quality improvement activities 【Effects of Implementation】 - Reduction in failure response time - Early resolution of quality issues - Promotion of knowledge transfer - Reduction in quality management costs

In the field of railway operation management, ensuring the safe operation of trains is the top priority, and in the event of a malfunction, prompt and accurate responses are required. It is important to effectively utilize past malfunction cases and inspection records to investigate causes and streamline recovery efforts. The AI-FTA Agent addresses these challenges by automatically organizing the causal relationships of malfunction causes, priorities for verification, and supporting documentation based on past malfunction reports, inspection records, and equipment data, thereby assisting in rapid decision-making on-site. 【Usage Scenarios】 * Identifying causes during abnormal detection in the operation management system * Identifying malfunction causes during inspection work at vehicle bases * Troubleshooting support for crew members 【Benefits of Implementation】 * Reduction in malfunction response time * Inheritance of know-how from veteran personnel * Moving away from person-dependent responses * Ensuring safe operations

We would like to introduce our AI platform for utilizing past trouble data, 'Causation.' AI structures and enables searchability of defect reports and maintenance records that are scattered across Excel and paper into a past trouble database. Similar troubles and past countermeasures can be queried in seconds, and reports for root cause analysis, 8D, and recurrence prevention are generated as drafts from the data. The probability of occurrence and the effectiveness of countermeasures (approximately 1/N) are calculated by a deterministic analysis engine, and the LLM does not generate numbers. Adoption and approval are always conducted by humans, ensuring that records are kept for audit compliance. 【Features】 ■ Drafting of recurrence prevention, 8D, and root cause analysis from data ■ Operable with open models ranging from 70B to 120B class ■ Supports internal LLM and on-premises (closed environment) provision ■ Free "Past Trouble Checkup" (5 business days) available to verify the extraction accuracy of your data *For more details, please download the PDF or feel free to contact us.