Prosecution Insights
Prosecution Insights
4 pending office actions • 2 art units • 4 examiners • 0 of 4 (0%) have an AI response strategy ready • 2 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 (25%) |
| §103 only | 1 (25%) |
| Double-patenting only | 1 (25%) |
| Multi-statute (no §101) | 1 (25%) |
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 |
|---|---|---|---|
| HSU, AMY R | 1 | 86.5% | -1.2% |
| THOMPSON, JAMES A | 1 | 85.1% | +3.4% |
| SHARMA, NEERAJ | 1 | 84.8% | +11.9% |
| WU, BENJAMIN C | 1 | 87.5% | +16.3% |
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 |
|---|---|---|---|
| 18649868 | QUERY OF VIDEO SUBJECT MATTER | SHARMA, NEERAJ | 56d overdue |
| 19082045 | APPEARANCE INFILLING IN VIDEO | THOMPSON, JAMES A | — |
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 |
|---|---|---|---|
| 19091656 | ROBOTIC CONTROL USING NATURAL LANGUAGE COMMANDS | HSU, AMY R | — |
| 18626231 | CLOUD-BASED FLEET AND ASSET MANAGEMENT FOR EDGE COMPUTING OF MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE WORKLOADS | WU, BENJAMIN C | — |
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 2 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18649868 | QUERY OF VIDEO SUBJECT MATTER | SHARMA, NEERAJ | 56d overdue |
| 18626231 | CLOUD-BASED FLEET AND ASSET MANAGEMENT FOR EDGE COMPUTING OF MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE WORKLOADS | WU, BENJAMIN C | — |
| Art Unit | Apps |
|---|---|
| 2659 | 1 |
| 2195 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 19091656 | ROBOTIC CONTROL USING NATURAL LANGUAGE COMMANDS | HSU, AMY R | — | §102§103Other | Non-Final OA | — | Pending | Mar 26, 2025 |
| 19082045 | APPEARANCE INFILLING IN VIDEO | THOMPSON, JAMES A | — | DP | Non-Final OA | — | Pending | Mar 17, 2025 |
| 18649868 | QUERY OF VIDEO SUBJECT MATTER | SHARMA, NEERAJ | 2659 | §103 | Final Rejection | 56d overdue | Pending | Apr 29, 2024 |
| 18626231 | CLOUD-BASED FLEET AND ASSET MANAGEMENT FOR EDGE COMPUTING OF MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE WORKLOADS | WU, BENJAMIN C | 2195 | §101 | Non-Final OA | — | Pending | Apr 03, 2024 |
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