Prosecution Insights
Prosecution Insights
4 pending office actions • 3 art units • 4 examiners • 0 of 4 (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. 3 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. 3 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 | 1 (25%) |
| §101 + other | 3 (75%) |
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 |
|---|---|---|---|
| PRASAD, NANCY N | 1 | 21.3% | +18.2% |
| GAVIN, KRISTIN ELIZABETH | 1 | 14.9% | +16.7% |
| NGUYEN, CHAU T | 1 | 67.9% | +30.9% |
| SMITH, CHENECA | 1 | 70.0% | +47.1% |
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 |
|---|---|---|---|
| 18136985 | System and Method for Optimized Training of a Neural Network Model for Data Extraction | NGUYEN, CHAU T | 42d overdue |
| 17985458 | SYSTEM AND METHOD FOR OPTIMIZED MODERNIZATION OF APPLICATIONS | SMITH, CHENECA | 30d overdue |
| 19020387 | GEN AI-BASED SYSTEM AND METHOD FOR ITERATIVE REFINEMENT OF INNOVATION DATA USING QUALITY SCORE | PRASAD, NANCY N | 15d |
| 18371096 | SYSTEM AND METHOD FOR DEVELOPING UNIFIED DIGITAL PLATFORM BASED VIRTUAL POWER BANKS | GAVIN, KRISTIN ELIZABETH | — |
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 |
|---|---|---|---|
| 18136985 | System and Method for Optimized Training of a Neural Network Model for Data Extraction | NGUYEN, CHAU T | 42d overdue |
| 17985458 | SYSTEM AND METHOD FOR OPTIMIZED MODERNIZATION OF APPLICATIONS | SMITH, CHENECA | 30d overdue |
| 19020387 | GEN AI-BASED SYSTEM AND METHOD FOR ITERATIVE REFINEMENT OF INNOVATION DATA USING QUALITY SCORE | PRASAD, NANCY N | 15d |
| 18371096 | SYSTEM AND METHOD FOR DEVELOPING UNIFIED DIGITAL PLATFORM BASED VIRTUAL POWER BANKS | GAVIN, KRISTIN ELIZABETH | — |
| Art Unit | Apps |
|---|---|
| 3624 | 2 |
| 2145 | 1 |
| 2192 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 19020387 | GEN AI-BASED SYSTEM AND METHOD FOR ITERATIVE REFINEMENT OF INNOVATION DATA USING QUALITY SCORE | PRASAD, NANCY N | 3624 | §101§103 | Final Rejection | 15d | Pending | Jan 14, 2025 |
| 18371096 | SYSTEM AND METHOD FOR DEVELOPING UNIFIED DIGITAL PLATFORM BASED VIRTUAL POWER BANKS | GAVIN, KRISTIN ELIZABETH | 3624 | §101§103 | Final Rejection | — | Pending | Sep 21, 2023 |
| 18136985 | System and Method for Optimized Training of a Neural Network Model for Data Extraction | NGUYEN, CHAU T | 2145 | §101§103 | Final Rejection | 42d overdue | Pending | Apr 20, 2023 |
| 17985458 | SYSTEM AND METHOD FOR OPTIMIZED MODERNIZATION OF APPLICATIONS | SMITH, CHENECA | 2192 | §101 | Non-Final OA | 30d overdue | Pending | Nov 11, 2022 |
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