What problems does "Ontology Boost" solve?

It solves the problem of generative AI failing to understand company-specific terminology and business rules, leading to irrelevant answers. It provides a foundation for AI to reference company-specific knowledge.

What is "Hearing AI"?

It is SiNCE's proprietary technology that structures and accumulates the experience and judgment criteria of veteran employees, which are difficult to document, through voice interviews.

What data is required for implementation?

A perfect data foundation is not necessary. You can start with existing scattered documents and begin accumulating knowledge in as little as 4 weeks.

Which companies should consider implementing this service?

It is suitable for companies that want to utilize generative AI but feel its understanding of their business is insufficient, or those who wish to retain the knowledge of veteran employees within the organization.

Is there post-implementation support?

Yes, we provide one-stop support from construction and connection to operation, ensuring continuous support after implementation.

AI News NQ Analysis

Grant Your Company's Business Knowledge to Generative AI: SiNCE Launches "Ontology Boost" Service for Ontology Construction and Operation Support

Key facts

Grant Your Company's Business Knowledge to Generative AI: SiNCE Launches "Ontology Boost" Service for Ontology Construction and Operation Support
SiNCE Inc. has launched "Ontology Boost," a new service that provides one-stop support for building, connecting, and operating an ontology, a knowledge base that enables generative AI to correctly understand a company's business knowledge. This allows users to elicit grounded answers from major generative AI models, overcoming the hurdles of AI utilization.
Source: PR TIMES
Date: Tue Jun 09 2026 20:21:07 GMT+0900 (Japan Standard Time)

Direct answer

SiNCE Inc. has launched "Ontology Boost," a new service that provides one-stop support for building, connecting, and operating an ontology, a knowledge base that enables generative AI to correctly understand a company's business knowledge. This allows users to elicit grounded answers from major generative AI models, overcoming the hurdles of AI utilization.

Citation: Grant Your Company's Business Knowledge to Generative AI: SiNCE Launches "Ontology Boost" Service for Ontology Construction and Operation Support (Tue Jun 09 2026 20:21:07 GMT+0900 (Japan Standard Time)), PR TIMES
Source: PR TIMES
Date: Tue Jun 09 2026 20:21:07 GMT+0900 (Japan Standard Time)

AI Summary (NQ-processed)

SiNCE Inc. has launched "Ontology Boost," a new service that provides one-stop support for building, connecting, and operating an ontology, a knowledge base that enables generative AI to correctly understand a company's business knowledge. This allows users to elicit grounded answers from major generative AI models, overcoming the hurdles of AI utilization.

AI Analysis

Frequently Asked Questions

Q: What problems does "Ontology Boost" solve?: A: It solves the problem of generative AI failing to understand company-specific terminology and business rules, leading to irrelevant answers. It provides a foundation for AI to reference company-specific knowledge.
Q: What is "Hearing AI"?: A: It is SiNCE's proprietary technology that structures and accumulates the experience and judgment criteria of veteran employees, which are difficult to document, through voice interviews.
Q: What data is required for implementation?: A: A perfect data foundation is not necessary. You can start with existing scattered documents and begin accumulating knowledge in as little as 4 weeks.
Q: Which companies should consider implementing this service?: A: It is suitable for companies that want to utilize generative AI but feel its understanding of their business is insufficient, or those who wish to retain the knowledge of veteran employees within the organization.
Q: Is there post-implementation support?: A: Yes, we provide one-stop support from construction and connection to operation, ensuring continuous support after implementation.