Tech Center 2400 • Art Units: 2493
This examiner grants 0% of resolved cases
Komi Nounyanou Amevigbe is an examiner in Tech Center 2400 and Art Unit 2493. The data for this examiner is currently very limited, with only 2 resolved cases on record. Both of these cases resulted in an allowance rate of 0.0 percent, which suggests a difficult start for applications assigned to this docket. The median days to allowance for the cases handled by this examiner is 1438, indicating a long wait for a final resolution.
The interview lift is also recorded at 0.0 percent. With only 2 resolved cases, it is difficult to draw broad conclusions about long-term trends or the effectiveness of specific strategies. However, the 1438-day median suggests that prosecution in this art unit can be a slow process. Practitioners should note the current lack of successful outcomes in the available data and prepare for a potentially rigorous examination. As more cases are resolved in Tech Center 2400, these metrics may provide more actionable insights for future applicants.
| App # | Title | Status | Assignee |
|---|---|---|---|
| 18921098 | DATA MANAGEMENT METHOD, SYSTEM, AND DEVICE | Final Rejection | HUAWEI TECHNOLOGIES CO., LTD. |
| 17954133 | CYBER-PHYSICAL PROTECTIONS FOR EDGE COMPUTING PLATFORMS | Non-Final OA | Intel Corporation |
| 18850041 | SEMI-FRAGILE NEURAL WATERMARKS FOR MEDIA AUTHENTICATION AND COUNTERING DEEPFAKES | Final Rejection | The Regents of the University of California |
| 18916046 | ATTACK ANALYSIS DEVICE, ATTACK ANALYSIS METHOD, AND COMPUTER READABLE MEDIUM | Final Rejection | Mitsubishi Electric Corporation |
| 19282199 | GENERATIVE ARTIFICIAL INTELLIGENCE-BASED SYSTEMS AND METHODS FOR IDENTIFYING ANOMALOUS DATA | Non-Final OA | State Farm Mutual Automobile Insurance Company |
| 18909237 | SYSTEMS AND METHODS FOR DATA ACCESS MANAGEMENT USING ADVANCED COMPUTATIONAL MODELS FOR DATA ANALYSIS AND AUTOMATED PROCESSING | Final Rejection | BANK OF AMERICA CORPORATION |
| 18945613 | Automatic Detection and Handling of Security-Related Anomalies by Utilizing Machine Learning and a Large Language Model | Final Rejection | VARONIS SYSTEMS, INC. |
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