Announced details
Security measures for generative AI models; practical deployment of generative AI by enterprises
Aims to reduce risks in generative AI models while limiting the time and costs associated with retraining (specific figures: Not disclosed)
ASGENT exhibited at Interop Tokyo 2026 and entered Hirundo in the award.
An award judged by a committee comprising key figures from leading media organizations and academic experts, recognizing new products from companies exhibiting at Interop Tokyo.
Best of Show Award Judges’ Special Award, Security (For AI) category
Best of Show Award Judges’ Committee
In this announcement the company addresses none of Contract Value / Offering price / Impact on Business Performance.
Interop Tokyo 2026 Best of Show Award Judges’ Committee
| Item | Details |
|---|---|
| Names of Products / Services Covered | Machine unlearning platform “Hirundo” |
| Counterparty | Interop Tokyo 2026 / Best of Show Award Judges’ Committee |
| Counterparty overview | An award judged by a committee comprising key figures from leading media organizations and academic experts, recognizing new products from companies exhibiting at Interop Tokyo. |
| Relationship with the Company | ASGENT exhibited at Interop Tokyo 2026 and entered Hirundo in the award. |
| Applicable area | Security measures for generative AI models; practical deployment of generative AI by enterprises |
| Award/certification name | Best of Show Award Judges’ Special Award, Security (For AI) category |
| Awarding / certifying body | Best of Show Award Judges’ Committee |
| Quantitative Effects | Aims to reduce risks in generative AI models while limiting the time and costs associated with retraining (specific figures: Not disclosed) |
| Source | Interop Tokyo 2026 Best of Show Award Judges’ Committee |
Items this document does not state (9)
These are items the company does not state in this document. We do not leave them blank, nor fill them in from other sources or by inference.
The reasons the company gives
The company's own explanation, not something inferred from the numbers.The award recognized the platform’s novel approach to diagnosing and correcting generative AI models themselves, reducing information leakage, hallucinations and bias, as well as its approach, which differs from conventional methods. The presentation, in which the developers participated and responded seriously to the judging process, was also recognized.