Prosecution Insights
Prosecution Insights
1 pending office actions • 0 art units • 1 examiners • 0 of 1 (0%) have an AI response strategy ready
2Genpen LLC currently has 1 pending office action. This action is assigned to 1 distinct examiner, and the data indicates 0 distinct art units for the portfolio. The 0 distinct art units figure reflects the current administrative state of the 1 pending office action.
The busiest examiner is NGUYEN, TIEN C, who is handling 1 pending office action. This 1 action constitutes the total 1 pending office actions for the company. With 1 distinct examiner managing the 1 pending action, the prosecution is entirely centralized. The 0 distinct art units metric provides a specific view into the current status of this single filing.
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 | 1 (100%) |
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 |
|---|---|---|---|
| NGUYEN, TIEN C | 1 | 68.1% | +18.5% |
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 |
|---|---|---|---|
| 19071128 | MACHINE LEARNING MODELS FOR QUALITATIVE DOMAINS | NGUYEN, TIEN 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 1 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 19071128 | MACHINE LEARNING MODELS FOR QUALITATIVE DOMAINS | NGUYEN, TIEN C | — |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 19071128 | MACHINE LEARNING MODELS FOR QUALITATIVE DOMAINS | NGUYEN, TIEN C | — | §101DP | Non-Final OA | — | Pending | Mar 05, 2025 |
IP Author helps IP teams respond to office actions faster with AI-generated responses, examiner analytics, and prosecution intelligence.
Start Free Trial