Prosecution Insights
Prosecution Insights
8 pending office actions • 8 art units • 8 examiners • 0 of 8 (0%) have an AI response strategy ready • 19 patents granted in the last 365 days
Based on the USPTO statutory response window for each pending office action. 8 of the docket's apps have a known mailing date; the rest are excluded from the tile counts.
Every pending office action with a known statutory deadline, placed on a days-until-due axis. Dots left of Today are overdue; the further right, the more runway. Cases that share a deadline window stack vertically. 8 of the docket's apps have a known mailing date.
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 | 5 (62%) |
| §103 only | 3 (38%) |
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 |
|---|---|---|---|
| YANG, QIAN | 1 | 73.7% | +31.1% |
| PHAM, KHANH B | 1 | 72.3% | +15.4% |
| ILES, TYLER EDWARD | 1 | 60.0% | +50.0% |
| MANG, VAN C | 1 | 75.7% | +26.2% |
| MILLER, JAMES H | 1 | 40.5% | +34.2% |
| MAC, GARY | 1 | 41.2% | +30.6% |
| RINES, ROBERT D | 1 | 38.4% | +46.4% |
| LIU, I JUNG | 1 | 62.1% | +33.8% |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 5 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 16681501 | Adaptive Fraud Detection | RINES, ROBERT D | 87d overdue |
| 17856648 | ADVANCED LEARNING SYSTEM FOR DETECTION AND PREVENTION OF MONEY LAUNDERING | MILLER, JAMES H | 19d overdue |
| 17732405 | MULTIUSER LEARNING SYSTEM FOR DETECTING A DIVERSE SET OF RARE BEHAVIOR | MAC, GARY | 1d overdue |
| 18629583 | NARRATIVE GENERATION PLATFORM FOR EXPLAINABLE PREDICTIVE CLASSIFIER | YANG, QIAN | 28d |
| 14796547 | MOBILE ATTRIBUTE TIME-SERIES PROFILING ANALYTICS | LIU, I JUNG | 63d |
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 8 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 16681501 | Adaptive Fraud Detection | RINES, ROBERT D | 87d overdue |
| 18069163 | FIRST-TO-SATURATE SINGLE MODAL LATENT FEATURE ACTIVATION FOR EXPLANATION OF MACHINE LEARNING MODELS | MANG, VAN C | 43d overdue |
| 17856648 | ADVANCED LEARNING SYSTEM FOR DETECTION AND PREVENTION OF MONEY LAUNDERING | MILLER, JAMES H | 19d overdue |
| 18349736 | PAIRWISE INTERACTION DETECTION TOOL | PHAM, KHANH B | 11d overdue |
| 17732405 | MULTIUSER LEARNING SYSTEM FOR DETECTING A DIVERSE SET OF RARE BEHAVIOR | MAC, GARY | 1d overdue |
| 18316987 | MULTI-VARIATE COUNTERFACTUAL DIFFUSION PROCESS | ILES, TYLER EDWARD | 14d |
| 18629583 | NARRATIVE GENERATION PLATFORM FOR EXPLAINABLE PREDICTIVE CLASSIFIER | YANG, QIAN | 28d |
| 14796547 | MOBILE ATTRIBUTE TIME-SERIES PROFILING ANALYTICS | LIU, I JUNG | 63d |
| Art Unit | Apps |
|---|---|
| 2677 | 1 |
| 2166 | 1 |
| 2122 | 1 |
| 2126 | 1 |
| 3694 | 1 |
| 2127 | 1 |
| 3625 | 1 |
| 3695 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18629583 | NARRATIVE GENERATION PLATFORM FOR EXPLAINABLE PREDICTIVE CLASSIFIER | YANG, QIAN | 2677 | §101 | Final Rejection | 28d | Pending | Apr 08, 2024 |
| 18349736 | PAIRWISE INTERACTION DETECTION TOOL | PHAM, KHANH B | 2166 | §103 | Non-Final OA | 11d overdue | Pending | Jul 10, 2023 |
| 18316987 | MULTI-VARIATE COUNTERFACTUAL DIFFUSION PROCESS | ILES, TYLER EDWARD | 2122 | §103 | Non-Final OA | 14d | Pending | May 12, 2023 |
| 18069163 | FIRST-TO-SATURATE SINGLE MODAL LATENT FEATURE ACTIVATION FOR EXPLANATION OF MACHINE LEARNING MODELS | MANG, VAN C | 2126 | §103 | Non-Final OA | 43d overdue | Pending | Dec 20, 2022 |
| 17856648 | ADVANCED LEARNING SYSTEM FOR DETECTION AND PREVENTION OF MONEY LAUNDERING | MILLER, JAMES H | 3694 | §101 | Non-Final OA | 19d overdue | Pending | Jul 01, 2022 |
| 17732405 | MULTIUSER LEARNING SYSTEM FOR DETECTING A DIVERSE SET OF RARE BEHAVIOR | MAC, GARY | 2127 | §101 | Non-Final OA | 1d overdue | Pending | Apr 28, 2022 |
| 16681501 | Adaptive Fraud Detection | RINES, ROBERT D | 3625 | §101 | Non-Final OA | 87d overdue | Pending | Nov 12, 2019 |
| 14796547 | MOBILE ATTRIBUTE TIME-SERIES PROFILING ANALYTICS | LIU, I JUNG | 3695 | §101 | Non-Final OA | 63d | Pending | Jul 10, 2015 |
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