Prosecution Insights
Prosecution Insights
2 pending office actions • 2 art units • 2 examiners • 0 of 2 (0%) have an AI response strategy ready • 1 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 (50%) |
| §112 only | 1 (50%) |
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 |
|---|---|---|---|
| WAESCO, JOSEPH M | 1 | 47.3% | +42.5% |
| SMITH, CHENECA | 1 | 69.9% | +47.1% |
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 |
|---|---|---|---|
| 18809599 | METHOD FOR TRAINING A COARSE RANKING SCORING MODEL FOR E-COMMERCE COMMODITIES AND RELATED PRODUCTS | WAESCO, JOSEPH M | — |
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 |
|---|---|---|---|
| 18161630 | CLOUD APPLICATION ENGINE DEPLOYMENT METHOD FOR SHIELDING WEB FRAMEWORK FROM USERS AND APPARATUS, DEVICE AND STORAGE MEDIUM THEREOF | SMITH, CHENECA | 19d |
| 18809599 | METHOD FOR TRAINING A COARSE RANKING SCORING MODEL FOR E-COMMERCE COMMODITIES AND RELATED PRODUCTS | WAESCO, JOSEPH M | — |
| Art Unit | Apps |
|---|---|
| 3625 | 1 |
| 2192 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18809599 | METHOD FOR TRAINING A COARSE RANKING SCORING MODEL FOR E-COMMERCE COMMODITIES AND RELATED PRODUCTS | WAESCO, JOSEPH M | 3625 | §101 | Final Rejection | — | Pending | Aug 20, 2024 |
| 18161630 | CLOUD APPLICATION ENGINE DEPLOYMENT METHOD FOR SHIELDING WEB FRAMEWORK FROM USERS AND APPARATUS, DEVICE AND STORAGE MEDIUM THEREOF | SMITH, CHENECA | 2192 | §112 | Non-Final OA | 19d | Pending | Jan 30, 2023 |
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