Prosecution Insights
Prosecution Insights
Technology area: Computing & Software
9 pending office actions • 6 art units • 9 examiners • 0 of 9 (0%) have an AI response strategy ready • 31 patents granted in the last 365 days
DeepX Co., Ltd. currently has 9 pending office actions in the Computing & Software technology area. These 9 pending office actions are distributed among 9 distinct examiners, meaning every pending matter is being handled by a different individual. The prosecution spans 6 distinct art units, which indicates that the company's software innovations are being evaluated across several different specialized groups within the USPTO.
The busiest examiner, CHEN, XUXING, is responsible for 1 busiest examiner pending action, reflecting the lack of examiner overlap across the 9 pending office actions. For practitioners, this means there is no central examiner to influence the broader portfolio's success. Instead, the 9 pending office actions require 9 independent strategies tailored to each of the 9 distinct examiners. The 6 distinct art units provide the organizational commonality for these 9 pending office actions, making the specific practices of those units a key factor in the portfolio's prosecution.
Based on the USPTO statutory response window for each pending office action. 1 of the docket's apps have a known mailing date; the rest are excluded from the tile counts.
Difficulty is derived from the rejection statutes on the most recent pending office action. §101-driven and multi-statute cases are graded Hard; §112-only and obviousness-type double-patenting cases are graded Easy; everything else is Medium. "Unknown" means we have not yet parsed a statute for that office action.
| Bucket | Cases |
|---|---|
| §103 only | 7 (78%) |
| Double-patenting only | 1 (11%) |
| Multi-statute (no §101) | 1 (11%) |
How the docket's pending cases split across USPTO tech-center bands.
Manual office-action response work runs about 10 hours per case. The time-saved bands below show what IP Author's prosecution pipeline typically delivers — a conservative 20% on the low end, 35% in the middle, 50% on the high end.
| Examiner | Apps on this docket | Allow rate | Interview lift |
|---|---|---|---|
| CHEN, XUXING | 1 | 86.1% | +11.6% |
| HUISMAN, DAVID J | 1 | 57.8% | +34.0% |
| BATAILLE, PIERRE MICHE | 1 | 92.9% | +6.1% |
| ILES, TYLER EDWARD | 1 | 55.6% | +66.7% |
| KWON, JUN | 1 | 41.0% | +47.2% |
| LEE, CHUN KUAN | 1 | 68.4% | +3.7% |
| GODO, MORIAM MOSUNMOLA | 1 | 45.0% | +37.4% |
| BENNETT, STUART D | 1 | 69.1% | -14.1% |
| KAPOOR, DEVAN | 1 | 7.1% | +11.1% |
Cases in front of an examiner with an allow rate of 80%+ where the difficulty is Easy or Medium. The top 2 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18918137 | ELECTRONIC DEVICE FOR SWITCHING MODE BY PROCESSING SENSING DATA AND SYSTEM USING THE SAME | CHEN, XUXING | 56d |
| 18678072 | NPU WITH CAPABILITY OF BUILT-IN SELF-TEST | BATAILLE, PIERRE MICHE | — |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 2 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18784455 | NPU, SOC AND ELECTRONIC DEVICE FOR CONTROLLING PEAK POWER BY DIVIDING CLOCK | HUISMAN, DAVID J | — |
| 17547158 | METHOD AND SYSTEM FOR BIT QUANTIZATION OF ARTIFICIAL NEURAL NETWORK | KAPOOR, DEVAN | — |
Cases in front of an examiner whose interview lift is 10 percentage points or more — i.e. interviewed cases historically resolve more favorably than non-interviewed ones. The top 6 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18918137 | ELECTRONIC DEVICE FOR SWITCHING MODE BY PROCESSING SENSING DATA AND SYSTEM USING THE SAME | CHEN, XUXING | 56d |
| 18784455 | NPU, SOC AND ELECTRONIC DEVICE FOR CONTROLLING PEAK POWER BY DIVIDING CLOCK | HUISMAN, DAVID J | — |
| 18639195 | METHOD AND STORAGE MEDIUM FOR QUANTIZING GRAPH-BASED NEURAL NETWORK MODEL WITH OPTIMIZED PARAMETERS | ILES, TYLER EDWARD | — |
| 18603346 | METHOD AND STORAGE MEDIUM FOR CONVERTING NON-GRAPH BASED ANN MODEL TO GRAPH BASED ANN MODEL | KWON, JUN | — |
| 18230912 | DATA MANAGEMENT DEVICE FOR SUPPORTING HIGH SPEED ARTIFICIAL NEURAL NETWORK OPERATION BY USING DATA CACHING BASED ON DATA LOCALITY OF ARTIFICIAL NEURAL NETWORK | GODO, MORIAM MOSUNMOLA | — |
| 17547158 | METHOD AND SYSTEM FOR BIT QUANTIZATION OF ARTIFICIAL NEURAL NETWORK | KAPOOR, DEVAN | — |
| Art Unit | Apps |
|---|---|
| 2176 | 1 |
| 2100 | 1 |
| 2827 | 1 |
| 2148 | 1 |
| 2481 | 1 |
| 2126 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18918137 | ELECTRONIC DEVICE FOR SWITCHING MODE BY PROCESSING SENSING DATA AND SYSTEM USING THE SAME | CHEN, XUXING | 2176 | §103Other | Non-Final OA | 56d | Pending | Oct 17, 2024 |
| 18784455 | NPU, SOC AND ELECTRONIC DEVICE FOR CONTROLLING PEAK POWER BY DIVIDING CLOCK | HUISMAN, DAVID J | 2100 | §102§103Other | Final Rejection | — | Pending | Jul 25, 2024 |
| 18678072 | NPU WITH CAPABILITY OF BUILT-IN SELF-TEST | BATAILLE, PIERRE MICHE | 2827 | DP | Non-Final OA | — | Pending | May 30, 2024 |
| 18639195 | METHOD AND STORAGE MEDIUM FOR QUANTIZING GRAPH-BASED NEURAL NETWORK MODEL WITH OPTIMIZED PARAMETERS | ILES, TYLER EDWARD | — | §103 | Non-Final OA | — | Pending | Apr 18, 2024 |
| 18603346 | METHOD AND STORAGE MEDIUM FOR CONVERTING NON-GRAPH BASED ANN MODEL TO GRAPH BASED ANN MODEL | KWON, JUN | — | §103Other | Non-Final OA | — | Pending | Mar 13, 2024 |
| 18594928 | Soc and system operated based on clock signals having different phases | LEE, CHUN KUAN | — | §103Other | Non-Final OA | — | Pending | Mar 04, 2024 |
| 18230912 | DATA MANAGEMENT DEVICE FOR SUPPORTING HIGH SPEED ARTIFICIAL NEURAL NETWORK OPERATION BY USING DATA CACHING BASED ON DATA LOCALITY OF ARTIFICIAL NEURAL NETWORK | GODO, MORIAM MOSUNMOLA | 2148 | §103 | Final Rejection | — | Pending | Aug 07, 2023 |
| 18312677 | NPU FOR ENCODING OR DECODING VIDEOSTREAM FORMAT FOR MACHINE ANALISYS | BENNETT, STUART D | 2481 | §103 | Final Rejection | — | Pending | May 05, 2023 |
| 17547158 | METHOD AND SYSTEM FOR BIT QUANTIZATION OF ARTIFICIAL NEURAL NETWORK | KAPOOR, DEVAN | 2126 | §103 | Non-Final OA | — | Pending | Dec 09, 2021 |
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