Prosecution Insights
Prosecution Insights
4 pending office actions • 3 art units • 4 examiners • 0 of 4 (0%) have an AI response strategy ready • 14 patents granted in the last 365 days
Based on the USPTO statutory response window for each pending office action. 2 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 |
|---|---|
| §101 only | 1 (25%) |
| §103 only | 3 (75%) |
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 |
|---|---|---|---|
| ZHAO, LEI | 1 | 73.5% | +21.6% |
| VINCENT, DAVID ROBERT | 1 | 80.5% | +4.4% |
| THOMAS, SOUMYA | 1 | 75.0% | +33.3% |
| SALEH, ZAID MUHAMMAD | 1 | 67.3% | +45.0% |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 1 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18209932 | SYSTEM AND METHOD FOR NEURAL NETWORK STRUCTURE-LEVEL QUANTIZATION OPTIMIZATION | VINCENT, DAVID ROBERT | — |
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 3 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18140445 | CHIP BASED LIDAR 3D OBJECT DETECTION SYSTEM AND METHOD | THOMAS, SOUMYA | 4d overdue |
| 17980322 | SMART SCENE BASED IMAGE CROPPING | SALEH, ZAID MUHAMMAD | 85d |
| 18232602 | 2-D REAL-TIME PEDESTRIAN POSE ESTIMATION MODEL FOR AUTONOMOUS DRIVING SYSTEMS | ZHAO, LEI | — |
| Art Unit | Apps |
|---|---|
| 2668 | 2 |
| 2123 | 1 |
| 2664 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18232602 | 2-D REAL-TIME PEDESTRIAN POSE ESTIMATION MODEL FOR AUTONOMOUS DRIVING SYSTEMS | ZHAO, LEI | 2668 | §103 | Final Rejection | — | Pending | Aug 10, 2023 |
| 18209932 | SYSTEM AND METHOD FOR NEURAL NETWORK STRUCTURE-LEVEL QUANTIZATION OPTIMIZATION | VINCENT, DAVID ROBERT | 2123 | §101 | Non-Final OA | — | Pending | Jun 14, 2023 |
| 18140445 | CHIP BASED LIDAR 3D OBJECT DETECTION SYSTEM AND METHOD | THOMAS, SOUMYA | 2664 | §103 | Final Rejection | 4d overdue | Pending | Apr 27, 2023 |
| 17980322 | SMART SCENE BASED IMAGE CROPPING | SALEH, ZAID MUHAMMAD | 2668 | §103 | Non-Final OA | 85d | Pending | Nov 03, 2022 |
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