LIGHTz Product Lineup

For Elevators: General Knowledge AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was decided" but also "why that decision was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during trouble response. 【Usage Scenarios】 - Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allow younger or other department members to independently search and reference past decision-making bases. - Early identification of risks from project documents during the design and production preparation stages. - Quickly respond to issues based on similar cases and countermeasures when problems arise. 【Implementation Effects】 - Visualization and inheritance of judgment criteria that were previously personalized. - Utilization of knowledge that not only allows for searches but also explains "why." - Reduction of rework through early detection of risks. - Shortening of lead times for trouble response.

• others

For refrigeration equipment: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experiences and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why that judgment was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during trouble response. 【Usage Scenarios】 ■ Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans ■ Allowing younger or other department members to independently search and reference past judgment bases ■ Early identification of risks from project documents during the design and production preparation stages ■ Rapid response to issues based on similar cases and countermeasures when problems arise 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that were previously personalized ■ Utilization of knowledge that not only allows for search but also understanding of "why" ■ Reduction of rework through early detection of risks ■ Shortening of lead time for trouble response

• others

For air conditioning equipment: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as the company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing for searches and references not only on "what was judged" but also on "why that judgment was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, linked searches between 3D drawings and knowledge, and the provision of similar case examples during trouble response. 【Usage Scenarios】 - Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allowing younger members or those from other departments to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Rapid response to troubles based on similar cases and countermeasures. 【Implementation Effects】 - Visualization and inheritance of judgment criteria that had become personalized. - Utilization of knowledge that not only allows for searches but also explains "why." - Reduction of rework through early detection of risks. - Shortening of lead times for trouble response.

• others

For measurement equipment: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing searches and references not only for "what was judged" but also for "why that judgment was made." It features AI agent functions that address various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during troubleshooting. 【Usage Scenarios】 ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger or other department members to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Quickly respond to issues based on similar cases and countermeasures when problems arise. 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that had become personalized. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time for troubleshooting responses.

• others

For sensors: Generalized AI is a manufacturing industry-specific organizational knowledge AI platform that naturally accumulates the tacit knowledge of experts from daily operations and conversations, allowing it to be utilized as the company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, enabling searches and references not only for "what was judged" but also for "why that judgment was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, linked searches between 3D drawings and knowledge, and presenting similar cases during troubleshooting. 【Usage Scenarios】 ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger members and those from other departments to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Respond quickly to issues based on similar cases and countermeasures when problems arise. 【Implementation Effects】 ■ Visualization and inheritance of previously personalized judgment criteria. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time for troubleshooting responses.

• others

For Display: General Knowledge AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions that address various aspects of business, such as risk detection in project documents, linked searches between 3D drawings and knowledge, and presenting similar cases during trouble response. [Usage Scenarios] ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger members or those from other departments to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Respond quickly during trouble occurrences based on similar cases and countermeasures. [Implementation Effects] ■ Visualization and inheritance of judgment criteria that had become personalized. ■ Utilization of knowledge that not only allows for searches but also understanding of "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time for trouble response.

• others

For semiconductor back-end processes: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a manufacturing industry-specific organizational knowledge AI platform that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during trouble response. 【Usage Scenarios】 ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger or other department members to independently search and reference past judgment bases. ■ Identify risks early from project documents during the design and production preparation stages. ■ Respond quickly to troubles based on similar cases and countermeasures. 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that had become personalized. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time for trouble response.

• others

For battery storage: The general-purpose AI for knowledge accumulation naturally gathers the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a "knowledge infrastructure" for companies. It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing searches and references not only to "what was judged" but also to "why it was judged that way." It features AI agent functions that address various aspects of operations, such as risk detection in project documents, linked searches between 3D drawings and knowledge, and presenting similar cases during troubleshooting. 【Usage Scenarios】 ■ Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans ■ Allowing younger or other department members to independently search and reference past judgment bases ■ Early identification of risks from project documents during the design and production preparation stages ■ Responding quickly to issues based on similar cases and countermeasures when problems arise 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that had become personalized ■ Utilization of knowledge that not only allows for searches but also explains "why" ■ Reduction of rework through early detection of risks ■ Shortening of lead time for troubleshooting responses

• others

For wind power generation: Generalized AI is a manufacturing industry-specific organizational knowledge AI platform that naturally accumulates the tacit knowledge of experts from daily operations and conversations, enabling it to be utilized as the company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why that judgment was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during troubleshooting. 【Usage Scenarios】 ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger or other department members to independently search and reference past judgment bases. ■ Identify risks early from project documents during the design and production preparation stages. ■ Respond quickly to issues based on similar cases and countermeasures when problems arise. 【Implementation Effects】 ■ Visualization and inheritance of previously personalized judgment criteria. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time in troubleshooting responses.

• others

For solar power generation: The general knowledge AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a "knowledge infrastructure" for companies. It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches between 3D drawings and knowledge, and presenting similar cases during troubleshooting. [Usage Scenarios] ■ Retaining judgment criteria and experiential knowledge before the retirement or transfer of veterans ■ Allowing younger employees and members from other departments to independently search and reference past judgment bases ■ Early identification of risks from project documents during the design and production preparation stages ■ Rapid response during trouble occurrences based on similar cases and countermeasures [Implementation Effects] ■ Visualization and inheritance of judgment criteria that had become personalized ■ Utilization of knowledge that not only allows for searches but also explains "why" ■ Reduction of rework through early detection of risks ■ Shortening of lead time for troubleshooting responses

• others

For recycling facilities: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a manufacturing industry-specific organizational knowledge AI platform that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing for searches and references not only on "what was judged" but also on "why that judgment was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and the presentation of similar cases during troubleshooting. 【Usage Scenarios】 ■ Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allowing younger or members from other departments to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Rapid response to issues based on similar cases and countermeasures when problems occur. 【Implementation Effects】 ■ Visualization and inheritance of previously personalized judgment criteria. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time for troubleshooting responses.

• others

For waste management: Generalized AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why that judgment was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and the presentation of similar cases during trouble response. 【Usage Scenarios】 ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger or members from other departments to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Rapid response to issues based on similar cases and countermeasures when problems arise. 【Implementation Effects】 ■ Visualization and inheritance of previously personalized judgment criteria. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time for trouble response.

• others

For environmental plants: Generalized AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions that address various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during troubleshooting. [Usage Scenarios] - Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allowing younger or other department members to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Responding quickly to issues based on similar cases and countermeasures when problems arise. [Implementation Effects] - Visualization and inheritance of judgment criteria that had become personalized. - Utilizing knowledge that not only allows for searches but also explains "why." - Reducing rework through early detection of risks. - Shortening lead times for troubleshooting responses.

• others

For water supply and drainage: The general-purpose AI for knowledge management naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a "knowledge infrastructure" for companies. It is a specialized organizational knowledge AI platform for the manufacturing industry. By structuring the experience and judgment criteria of veterans from internal documents and conversation records, it allows users to search and reference not only "what was judged" but also "why that judgment was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and the presentation of similar cases during trouble response. [Usage Scenarios] - Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allowing younger or other department members to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Rapid response to issues based on similar cases and countermeasures when problems arise. [Implementation Effects] - Visualization and inheritance of judgment criteria that had become personalized. - Utilization of knowledge that not only allows for searches but also explains "why." - Reduction of rework through early detection of risks. - Shortening of lead time for trouble response.

• others

For power generation equipment: General-purpose AI is a manufacturing industry-specific organizational knowledge AI platform that naturally accumulates the tacit knowledge of experts from daily operations and conversations, enabling it to be utilized as the company's "knowledge infrastructure." It structures and accumulates the experiences and judgment criteria of veterans from internal documents and conversation records, allowing searches and references not only for "what was judged" but also for "why it was judged that way." It features AI agent functions that address various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during trouble response. 【Usage Scenarios】 ■ Preserve judgment criteria and experiential knowledge as knowledge before veterans retire or transfer. ■ Allow younger or other department members to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Respond quickly to troubles based on similar cases and countermeasures. 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that were previously personalized. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early risk detection. ■ Shortening of lead time for trouble response.

• others

For the energy sector: The general-purpose AI for knowledge accumulation naturally gathers the tacit knowledge of experts from daily operations and conversations, serving as a "knowledge infrastructure" for companies through a manufacturing industry-specific organizational knowledge AI platform. It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was decided" but also "why that decision was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during troubleshooting. 【Usage Scenarios】 ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger employees and members from other departments to independently search and reference past decision-making bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Quickly respond to issues based on similar cases and countermeasures when problems arise. 【Implementation Benefits】 ■ Visualization and inheritance of judgment criteria that were previously personalized. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time for troubleshooting responses.

• others

For warehouse systems: Generalized AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as the company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why that judgment was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and the presentation of similar cases during trouble response. 【Usage Scenarios】 ■ Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans ■ Allowing younger or other department members to independently search and reference past judgment bases ■ Early identification of risks from project documents during the design and production preparation stages ■ Rapid response to issues based on similar cases and countermeasures when troubles arise 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that had become personalized ■ Utilization of knowledge that not only allows for searches but also explains "why" ■ Reduction of rework through early detection of risks ■ Shortening of lead time in trouble response

• others

For logistics equipment: Generalized AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a manufacturing industry-specific organizational knowledge AI platform that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of business, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during trouble response. 【Usage Scenarios】 ■ Preserve judgment criteria and experiential knowledge as knowledge before veterans retire or transfer. ■ Allow younger employees and members from other departments to independently search and reference past judgment bases. ■ Identify risks early from project documents during the design and production preparation stages. ■ Respond quickly to issues based on similar cases and countermeasures when troubles arise. 【Implementation Effects】 ■ Visualization and inheritance of previously personalized judgment criteria. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time for trouble response.

• others

For packaging machinery: Generalized AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing searches and references not only to "what was judged" but also to "why that judgment was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches between 3D drawings and knowledge, and presenting similar cases during troubleshooting. 【Usage Scenarios】 - Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allowing younger or other department members to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Responding quickly during trouble occurrences based on similar cases and countermeasure proposals. 【Implementation Effects】 - Visualization and inheritance of judgment criteria that had become personalized. - Utilization of knowledge that not only allows for searches but also explains "why." - Reduction of rework through early detection of risks. - Shortening of lead times for trouble response.

• others

For printing: General-purpose AI for knowledge management naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a "knowledge infrastructure" for companies. It structures and stores the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was decided" but also "why that decision was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during troubleshooting. [Usage Scenarios] - Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allowing younger or members from other departments to independently search and reference past decision-making bases. - Early identification of risks from project documents during the design and production preparation stages. - Rapid response to issues based on similar cases and countermeasures when problems arise. [Implementation Effects] - Visualization and inheritance of previously personalized judgment criteria. - Utilization of knowledge that not only allows for searches but also explains "why." - Reduction of rework through early detection of risks. - Shortening of lead time in troubleshooting responses.

• others

For the textile industry: The general-purpose AI for knowledge accumulation naturally gathers the tacit knowledge of experts from daily operations and conversations, serving as a knowledge infrastructure for companies. It is a specialized organizational knowledge AI platform for the manufacturing industry. By structuring the experiences and judgment criteria of veterans from internal documents and conversation records, it allows for searching and referencing not only "what was judged" but also "why that judgment was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during trouble response. 【Usage Scenarios】 - Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allowing younger or other department members to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Rapid response to issues based on similar cases and countermeasures when problems arise. 【Implementation Effects】 - Visualization and inheritance of judgment criteria that had become personalized. - Utilization of knowledge that not only allows for searching but also understanding "why." - Reduction of rework through early risk detection. - Shortening of lead time in trouble response.

• others

For Glass Manufacturing: The General Knowledge AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experiences and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of business, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and the presentation of similar cases during trouble response. 【Usage Scenarios】 ■ Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans ■ Allowing younger or other department members to independently search and reference past judgment bases ■ Early identification of risks from project documents during the design and production preparation stages ■ Rapid response to troubles based on similar cases and countermeasures 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that had become personalized ■ Utilization of knowledge that not only allows for searching but also understanding "why" ■ Reduction of rework through early detection of risks ■ Shortening of lead time for trouble response

• others

For resin and plastic: The general-purpose AI accumulates the tacit knowledge of experts naturally from daily operations and conversations, serving as a manufacturing industry-specific organizational knowledge AI platform that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experiences and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, linked searches between 3D drawings and knowledge, and presenting similar cases during troubleshooting. 【Usage Scenarios】 - Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allowing younger or other department members to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Responding quickly to issues based on similar cases and countermeasures when problems arise. 【Implementation Effects】 - Visualization and inheritance of judgment criteria that had become personalized. - Utilizing knowledge that not only allows for searches but also explains "why." - Reducing rework through early detection of risks. - Shortening lead times for troubleshooting responses.

• others

For non-ferrous metals: The general-purpose AI for knowledge accumulation naturally gathers the tacit knowledge of experts from daily operations and conversations, serving as a "knowledge infrastructure" for companies through a manufacturing industry-specific organizational knowledge AI platform. It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during trouble response. 【Usage Scenarios】 ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger members or those from other departments to independently search and reference past judgment bases. ■ Identify risks early from project documents during the design and production preparation stages. ■ Respond quickly during trouble occurrences based on similar cases and countermeasures. 【Implementation Effects】 ■ Visualization and inheritance of previously personalized judgment criteria. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early risk detection. ■ Shortening of lead time for trouble response.

• others

For the steel industry: The general-purpose AI for knowledge accumulation naturally gathers the tacit knowledge of experts from daily operations and conversations, serving as a "knowledge infrastructure" for companies through a manufacturing-focused organizational knowledge AI platform. It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why that judgment was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during trouble response. 【Usage Scenarios】 ■ Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans ■ Allowing younger or other department members to independently search and reference past judgment bases ■ Early identification of risks from project documents during the design and production preparation stages ■ Rapid response to issues based on similar cases and countermeasures when problems arise 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that were previously personalized ■ Utilization of knowledge that not only allows for searches but also explains "why" ■ Reduction of rework through early detection of risks ■ Shortening of lead time for trouble response

• others

For cosmetics: The general knowledge AI for manufacturing is a specialized organizational knowledge AI platform that naturally accumulates the tacit knowledge of experts from daily operations and conversations, and can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions that address various aspects of operations, such as risk detection in project documents, linked searches between 3D drawings and knowledge, and presenting similar cases during troubleshooting. 【Usage Scenarios】 ■ Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allowing younger or members from other departments to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Rapid response during trouble occurrences based on similar cases and countermeasures. 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that had become personalized. ■ Utilization of knowledge that not only allows for searching but also understanding "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time for trouble response.

• others

For pharmaceuticals: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing for searches and references not only on "what was judged" but also on "why that judgment was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during trouble response. 【Usage Scenarios】 ■ Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans ■ Allowing younger or other department members to independently search and reference past judgment bases ■ Early identification of risks from project documents during the design and production preparation stages ■ Rapid response during trouble occurrences based on similar cases and countermeasures 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that had become personalized ■ Utilization of knowledge that not only allows for searches but also explains "why" ■ Reduction of rework through early detection of risks ■ Shortening of lead time for trouble response

• others

For agricultural machinery: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches between 3D drawings and knowledge, and presenting similar cases during troubleshooting. [Usage Scenarios] ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger members or those from other departments to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Respond quickly during trouble occurrences based on similar cases and countermeasure proposals. [Implementation Effects] ■ Visualization and inheritance of judgment criteria that were previously personalized. ■ Utilization of knowledge that not only allows for searching but also understanding "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time for troubleshooting responses.

• others

For construction machinery: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why that judgment was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, linked searches between 3D drawings and knowledge, and presenting similar cases during trouble response. [Usage Scenarios] - Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allow younger employees and members from other departments to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Respond quickly to troubles based on similar cases and countermeasure proposals. [Implementation Effects] - Visualization and inheritance of judgment criteria that had become personalized. - Utilization of knowledge that not only allows for search but also understanding of "why." - Reduction of rework through early detection of risks. - Shortening of lead time in trouble response.

• others

For communication equipment: Generalized AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing searches and references not only for "what was judged" but also for "why that judgment was made." It features AI agent functions tailored to various aspects of business, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during trouble response. [Usage Scenarios] ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger employees and members from other departments to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Respond quickly to issues based on similar cases and countermeasures when problems arise. [Implementation Effects] ■ Visualization and inheritance of judgment criteria that had become personalized. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead times for trouble response.

• others

For electronic components: The general-purpose AI for knowledge accumulation naturally gathers the tacit knowledge of experts from daily operations and conversations, serving as a "knowledge infrastructure" for companies. It is a manufacturing industry-specific organizational knowledge AI platform. By structuring the experiences and judgment criteria of veterans from internal documents and conversation records, it allows users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of business, such as risk detection in project documents, integrated searches between 3D drawings and knowledge, and presenting similar cases during troubleshooting. 【Usage Scenarios】 - Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allowing younger or other department members to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Rapid response during trouble occurrences based on similar cases and countermeasures. 【Implementation Effects】 - Visualization and inheritance of judgment criteria that were previously personalized. - Utilization of knowledge that not only allows for searches but also explains "why." - Reduction of rework through early detection of risks. - Shortening of lead time for trouble response.

• others

For semiconductor manufacturing equipment: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as the company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why that judgment was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, linked searches between 3D drawings and knowledge, and presenting similar cases during trouble response. [Usage Scenarios] - Preserving judgment criteria and experiential knowledge before the retirement or transfer of veterans. - Allowing younger or members from other departments to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Quickly responding to issues based on similar cases and countermeasures when problems arise. [Implementation Effects] - Visualization and inheritance of judgment criteria that had become personalized. - Utilizing knowledge that not only allows for searches but also explains "why." - Reducing rework through early detection of risks. - Shortening lead times for trouble response.

• others

For shipbuilding: The generalized knowledge AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a manufacturing industry-specific organizational knowledge AI platform that can be utilized as a company's "knowledge infrastructure." It structures and stores the experiences and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches between 3D drawings and knowledge, and presenting similar cases during trouble response. 【Usage Scenarios】 ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger employees and members from other departments to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation phases. ■ Quickly respond to issues based on similar cases and countermeasures when problems arise. 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that had become personalized. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time for trouble response.

• others

For EVs: The general-purpose AI for knowledge accumulation naturally gathers the tacit knowledge of experts from daily operations and conversations, serving as a "knowledge infrastructure" for manufacturing-specific organizational knowledge AI platforms. It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing searches and references not only to "what was judged" but also to "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during trouble response. 【Usage Scenarios】 ■ Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans ■ Allowing younger or other department members to independently search and reference past judgment bases ■ Early identification of risks from project documents during the design and production preparation stages ■ Rapid response to troubles based on similar cases and countermeasures 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that had become personalized ■ Utilization of knowledge that not only allows for searches but also explains "why" ■ Reduction of rework through early detection of risks ■ Shortening of lead time for trouble response

• others

For industrial machinery: The general-purpose AI for knowledge accumulation naturally gathers the tacit knowledge of experts from daily operations and conversations, serving as a "knowledge infrastructure" for companies. It is a manufacturing industry-specific organizational knowledge AI platform. By structuring knowledge from internal documents and conversation records, it accumulates the experiences and judgment criteria of veterans, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches between 3D drawings and knowledge, and presenting similar cases during troubleshooting. 【Usage Scenarios】 ■ Preserve judgment criteria and experiential knowledge as knowledge before veterans retire or transfer. ■ Allow younger or other department members to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Respond quickly to issues based on similar cases and countermeasures when problems arise. 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that were previously personalized. ■ Utilization of knowledge that not only allows for search but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time for troubleshooting responses.

• others

For heavy industry: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing sector that can be utilized as a company's "knowledge infrastructure." It structures and stores the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of business, such as risk detection in project documents, integrated searches between 3D drawings and knowledge, and presenting similar cases during trouble response. 【Usage Scenarios】 ■ Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans ■ Allowing younger or other department members to independently search and reference past judgment bases ■ Early identification of risks from project documents during the design and production preparation stages ■ Rapid response to issues based on similar cases and countermeasures when problems arise 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that had become personalized ■ Utilization of knowledge that not only allows for search but also understanding of "why" ■ Reduction of rework through early detection of risks ■ Shortening of lead time in trouble response

• others

For home appliances: General-purpose AI is a manufacturing industry-specific organizational knowledge AI platform that naturally accumulates the tacit knowledge of experts from daily operations and conversations, allowing it to be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, enabling searches and references not only for "what was judged" but also for "why it was judged that way." It features AI agent functions tailored to various aspects of business, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during trouble response. [Usage Scenarios] ■ Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans ■ Allowing younger or other department members to search and reference past judgment bases independently ■ Early identification of risks from project documents during the design and production preparation stages ■ Rapid response based on similar cases and countermeasures when troubles occur [Implementation Effects] ■ Visualization and inheritance of previously personalized judgment criteria ■ Utilization of knowledge that not only allows for searches but also explains "why" ■ Reduction of rework through early detection of risks ■ Shortening of lead time in trouble response

• others

For precision machinery: Generalized AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experiences and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions that address various aspects of operations, such as risk detection in project documents, integrated searches between 3D drawings and knowledge, and presenting similar cases during troubleshooting. 【Usage Scenarios】 ■ Preserving judgment criteria and experiential knowledge before the retirement or transfer of veterans. ■ Allowing younger employees and members from other departments to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Quickly responding to issues based on similar cases and countermeasures when problems arise. 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that had become personalized. ■ Utilizing knowledge that not only allows for searches but also explains "why." ■ Reducing rework through early detection of risks. ■ Shortening lead times for troubleshooting responses.

• others

For Robots: General Knowledge AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and stores the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches between 3D drawings and knowledge, and presenting similar cases during trouble response. 【Usage Scenarios】 ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger or other department members to independently search and reference past judgment bases. ■ Identify risks early from project documents during the design and production preparation stages. ■ Respond quickly to troubles based on similar cases and countermeasures. 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that had become personalized. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time for trouble response.

• others

For chemical plants: The general knowledge AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as the company's "knowledge infrastructure." It structures and stores the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why that judgment was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during trouble response. [Usage Scenarios] - Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allow younger members or those from other departments to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Respond quickly during trouble occurrences based on similar cases and countermeasure proposals. [Implementation Effects] - Visualization and inheritance of judgment criteria that had become personalized. - Utilization of knowledge that not only allows for searches but also provides understanding of "why." - Reduction of rework through early detection of risks. - Shortening of lead time in trouble response.

• others

For food machinery: Generalized AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a manufacturing industry-specific organizational knowledge AI platform that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during troubleshooting. 【Usage Scenarios】 ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger employees and members from other departments to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Quickly respond to issues based on similar cases and countermeasures when problems arise. 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that were previously personalized. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time for troubleshooting responses.

• others

For medical devices: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why that judgment was made." It features AI agent functions tailored to various aspects of business operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during troubleshooting. 【Usage Scenarios】 ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger employees and members from other departments to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Respond quickly to issues based on similar cases and countermeasures when problems arise. 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that were previously personalized. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortened lead time for troubleshooting responses.

• others

For industrial machinery: Generalized AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a manufacturing industry-specific organizational knowledge AI platform that can be utilized as a company's "knowledge infrastructure." It structures and stores the experiences and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was decided" but also "why that decision was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during troubleshooting. [Usage Scenarios] ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger or other department members to independently search and reference past decision-making bases. ■ Identify risks early from project documents during the design and production preparation stages. ■ Respond quickly during trouble occurrences based on similar cases and countermeasures. [Implementation Effects] ■ Visualization and inheritance of previously personalized judgment criteria. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead times for trouble response.

• others

For construction machinery parts: The general-purpose AI accumulates the tacit knowledge of experts naturally from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as the company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing searches and references not only for "what was judged" but also for "why it was judged that way." It features AI agent functions tailored to various aspects of business, such as risk detection in project documents, integrated searches linking 3D drawings and knowledge, and presenting similar cases during trouble response. 【Usage Scenarios】 ■ Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans ■ Allowing younger or other department members to independently search and reference past judgment bases ■ Early identification of risks from project documents during the design and production preparation stages ■ Rapid response to troubles based on similar cases and countermeasures 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that had become personalized ■ Utilization of knowledge that not only allows for searches but also explains "why" ■ Reduction of rework through early detection of risks ■ Shortening of lead time for trouble response

• others

For railway vehicle parts: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a manufacturing industry-specific organizational knowledge AI platform that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing for searches and references not only on "what was judged" but also on "why that judgment was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, linked searches between 3D drawings and knowledge, and presenting similar cases during troubleshooting. 【Usage Scenarios】 ■ Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans ■ Allowing younger or members from other departments to independently search and reference past judgment bases ■ Early identification of risks from project documents during the design and production preparation stages ■ Rapid response during trouble occurrences based on similar cases and countermeasures 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that had become personalized ■ Utilization of knowledge that not only allows for searches but also explains "why" ■ Reduction of rework through early detection of risks ■ Shortening of lead time for troubleshooting responses

• others