Prosecution Insights
Prosecution Insights
4 pending office actions • 2 art units • 3 examiners • 0 of 4 (0%) have an AI response strategy ready
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 + other | 3 (75%) |
| 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 |
|---|---|---|---|
| RODEN, DONALD THOMAS | 2 | 20.0% | +100.0% |
| MULLINAX, CLINT LEE | 1 | 46.9% | +36.8% |
| GIROUX, GEORGE | 1 | 65.5% | +26.7% |
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 |
|---|---|---|---|
| 18103672 | AUTOMATED SYNTHETIC AUGMENTATION OF MACHINE LEARNING MODEL TRAINING DATASETS AND INPUT VARIABLES TO IMPROVE ACCURACY | MULLINAX, CLINT LEE | 71d |
| 18103702 | SYSTEMS AND METHODS FOR IMPROVING THE STRUCTURAL DESIGN OF ARTIFICIAL INTELLIGENCE SYSTEMS THROUGH MODELING AND SIMULATION TECHNIQUES | GIROUX, GEORGE | — |
| 18103806 | ERROR DETECTION AND CORRECTION SYSTEMS FOR DATA PROCESSING IMPLEMENTED VIA ARTIFICIAL INTELLIGENCE | RODEN, DONALD THOMAS | — |
| 18103722 | SYSTEMS AND METHODS FOR DETECTING AND CORRECTING ERRORS IN DATA PROCESSING SYSTEMS IMPLEMENTED BY ARTIFICIAL INTELLIGENCE | RODEN, DONALD THOMAS | — |
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 4 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18103672 | AUTOMATED SYNTHETIC AUGMENTATION OF MACHINE LEARNING MODEL TRAINING DATASETS AND INPUT VARIABLES TO IMPROVE ACCURACY | MULLINAX, CLINT LEE | 71d |
| 18103702 | SYSTEMS AND METHODS FOR IMPROVING THE STRUCTURAL DESIGN OF ARTIFICIAL INTELLIGENCE SYSTEMS THROUGH MODELING AND SIMULATION TECHNIQUES | GIROUX, GEORGE | — |
| 18103806 | ERROR DETECTION AND CORRECTION SYSTEMS FOR DATA PROCESSING IMPLEMENTED VIA ARTIFICIAL INTELLIGENCE | RODEN, DONALD THOMAS | — |
| 18103722 | SYSTEMS AND METHODS FOR DETECTING AND CORRECTING ERRORS IN DATA PROCESSING SYSTEMS IMPLEMENTED BY ARTIFICIAL INTELLIGENCE | RODEN, DONALD THOMAS | — |
| Art Unit | Apps |
|---|---|
| 2128 | 3 |
| 2123 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18103672 | AUTOMATED SYNTHETIC AUGMENTATION OF MACHINE LEARNING MODEL TRAINING DATASETS AND INPUT VARIABLES TO IMPROVE ACCURACY | MULLINAX, CLINT LEE | 2123 | §101§103 | Non-Final OA | 71d | Pending | Jan 31, 2023 |
| 18103702 | SYSTEMS AND METHODS FOR IMPROVING THE STRUCTURAL DESIGN OF ARTIFICIAL INTELLIGENCE SYSTEMS THROUGH MODELING AND SIMULATION TECHNIQUES | GIROUX, GEORGE | 2128 | §102§103 | Final Rejection | — | Pending | Jan 31, 2023 |
| 18103806 | ERROR DETECTION AND CORRECTION SYSTEMS FOR DATA PROCESSING IMPLEMENTED VIA ARTIFICIAL INTELLIGENCE | RODEN, DONALD THOMAS | 2128 | §101§103DP | Non-Final OA | — | Pending | Jan 31, 2023 |
| 18103722 | SYSTEMS AND METHODS FOR DETECTING AND CORRECTING ERRORS IN DATA PROCESSING SYSTEMS IMPLEMENTED BY ARTIFICIAL INTELLIGENCE | RODEN, DONALD THOMAS | 2128 | §101§103DP | Non-Final OA | — | Pending | Jan 31, 2023 |
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