Prosecution Insights
Prosecution Insights
5 pending office actions • 3 art units • 5 examiners • 0 of 5 (0%) have an AI response strategy ready • 8 patents granted in the last 365 days
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 |
|---|---|
| §101 only | 1 (20%) |
| §101 + other | 2 (40%) |
| §103 only | 1 (20%) |
| Multi-statute (no §101) | 1 (20%) |
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 |
|---|---|---|---|
| SOFRONIOU, MICHAEL MARIO | 1 | 100.0% | +0.0% |
| LE, JOHN H | 1 | 87.9% | +7.0% |
| WALSH, EMMETT K | 1 | 52.7% | +19.9% |
| BEAN, GRIFFIN TANNER | 1 | 27.6% | +15.7% |
| GRUSZKA, DANIEL PATRICK | 1 | 50.0% | +100.0% |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 4 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18809217 | METHOD OF SETTING REGION OF INTEREST IN IMAGE FOR COLLECTING ROAD TRAFFIC INDEXES | SOFRONIOU, MICHAEL MARIO | — |
| 18627136 | DEVICE AND METHOD FOR PROVIDING BENCHMARK RESULT OF ARTIFICIAL INTELLIGENCE BASED MODEL | LE, JOHN H | — |
| 18395030 | APPARATUS AND METHOD FOR OPTIMIZING ARTIFICIAL INTELLIGENCE BASED MODEL | WALSH, EMMETT K | — |
| 18061305 | METHOD AND SYSTEM FOR OPTIMIZING QUANTIZATION MODEL | BEAN, GRIFFIN TANNER | — |
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 |
|---|---|---|---|
| 17842611 | METHOD AND APPARATUS FOR RETRAINING COMPRESSED MODEL USING VARIANCE EQUALIZATION | GRUSZKA, DANIEL PATRICK | 17d overdue |
| 18395030 | APPARATUS AND METHOD FOR OPTIMIZING ARTIFICIAL INTELLIGENCE BASED MODEL | WALSH, EMMETT K | — |
| 18061305 | METHOD AND SYSTEM FOR OPTIMIZING QUANTIZATION MODEL | BEAN, GRIFFIN TANNER | — |
| Art Unit | Apps |
|---|---|
| 2121 | 2 |
| 2661 | 1 |
| 2857 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18809217 | METHOD OF SETTING REGION OF INTEREST IN IMAGE FOR COLLECTING ROAD TRAFFIC INDEXES | SOFRONIOU, MICHAEL MARIO | 2661 | §103§112 | Non-Final OA | — | Pending | Aug 19, 2024 |
| 18627136 | DEVICE AND METHOD FOR PROVIDING BENCHMARK RESULT OF ARTIFICIAL INTELLIGENCE BASED MODEL | LE, JOHN H | 2857 | §101§103 | Non-Final OA | — | Pending | Apr 04, 2024 |
| 18395030 | APPARATUS AND METHOD FOR OPTIMIZING ARTIFICIAL INTELLIGENCE BASED MODEL | WALSH, EMMETT K | — | §101§103 | Non-Final OA | — | Pending | Dec 22, 2023 |
| 18061305 | METHOD AND SYSTEM FOR OPTIMIZING QUANTIZATION MODEL | BEAN, GRIFFIN TANNER | 2121 | §101 | Final Rejection | — | Pending | Dec 02, 2022 |
| 17842611 | METHOD AND APPARATUS FOR RETRAINING COMPRESSED MODEL USING VARIANCE EQUALIZATION | GRUSZKA, DANIEL PATRICK | 2121 | §103 | Non-Final OA | 17d overdue | Pending | Jun 16, 2022 |
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