The technologies behind TIGEREYE's AI are patented or patent pending.
The technologies behind TIGEREYE's AI are patented or patent pending.
01
Patent granted (Patent No. 7296538)
A technology that identifies individuals by focusing on how people walk and move, extracting features and differences from video. It can identify people even from distances where their faces are not visible, and it stands out for its speed and high recognition accuracy.
Because it identifies people in real time, it enables quick, accurate identity checks in security, entry and exit management, and more.
02
Joint patent application filed (Application No. 2026-016437)
KOKUYO's expertise in form-based work, and TIGEREYE's AI technology. Together, these two strengths gave rise to this patent-pending technology.
To solve the hard problems of form-based work, such as handwriting and complex layouts, the two companies jointly developed "Inference-Integrated OCR," a technology in which AI performs its own inference and correction.
03
Patent application filed (Application No. 2026-226420)
A proprietary AI model that predicts future changes in state and the next action to take, based on the current situation, past experience, goals, and action history.
It is a proprietary AI architecture that places the relationship between "State," "Action," and "Next State" at the center of learning.
04
Patent application filed (Application No. 2025-035944)
A technology that responds optimally and with intent, adapting to the situation of the user's dialogue. A camera reads facial expressions and scores understanding, interest, and emotional positivity. It determines the current stage from the flow of the dialogue, adjusts prompts to match the scores, and shapes the LLM's output.
It can be used in sales, customer support, education, healthcare, dialogue with robots, and more. Trinity Eye is based on this technology.
05
Joint patent application filed (Application No. 2025-180014)
A mechanism in which AI evaluates, selects, and learns from AI. The application was filed jointly with the aim of changing behavior in office spaces and improving intellectual productivity. Without people setting rules, the AI itself selects the combination that delivers the best results for the situation.
Three layers—dialogue (Talk), evaluation (Judge), and selection (Match)—work together to evaluate AI output against eight metrics and select the optimal combination of agents. Because it repeats the cycle of "evaluate, select, execute, learn," its accuracy and efficiency improve the more it is used.
Toward workplaces where AI is simply part of everyday work.
