Prosecution Insights
Prosecution Insights
Technology area: Transportation, E-Commerce & Mechanical Systems
2 pending office actions • 2 art units • 2 examiners • 0 of 2 (0%) have an AI response strategy ready
Argus Software Inc. has 2 pending office actions within the Transportation, E-Commerce & Mechanical Systems technology area. These actions are handled by 2 distinct examiners and are spread across 2 distinct art units. The count of 2 pending office actions matches the count of 2 distinct examiners. This workload is also distributed across 2 distinct art units, which is equal to the number of examiners.
The busiest examiner, NGUYEN, LIZ P, is responsible for 1 busiest examiner pending action. This 1 busiest examiner pending action is one of the 2 pending office actions in the total portfolio. Since there are 2 distinct examiners, the workload is divided between them. The 2 distinct art units suggest that the pending office actions cover different technical aspects of the Transportation, E-Commerce & Mechanical Systems sector. Practitioners will need to manage two separate prosecution tracks, each with its own examiner and art unit requirements. The 1 busiest examiner pending action assigned to NGUYEN, LIZ P represents one of the current active matters.
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%) |
| §101 + other | 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 |
|---|---|---|---|
| NGUYEN, LIZ P | 1 | 61.1% | +6.0% |
| MANEJWALA, ISMAIL A | 1 | 49.1% | +50.6% |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 2 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18598515 | GENERATION OF VISUALIZATIONS BASED ON MACHINE LEARNING OUTPUTS | NGUYEN, LIZ P | 28d overdue |
| 18498732 | METHOD AND SYSTEM FOR PROCESSING DATA USING MACHINE LEARNING MODELS | MANEJWALA, ISMAIL A | — |
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 |
|---|---|---|---|
| 18498732 | METHOD AND SYSTEM FOR PROCESSING DATA USING MACHINE LEARNING MODELS | MANEJWALA, ISMAIL A | — |
| Art Unit | Apps |
|---|---|
| 3696 | 1 |
| 3628 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18598515 | GENERATION OF VISUALIZATIONS BASED ON MACHINE LEARNING OUTPUTS | NGUYEN, LIZ P | 3696 | §101§103 | Final Rejection | 28d overdue | Pending | Mar 07, 2024 |
| 18498732 | METHOD AND SYSTEM FOR PROCESSING DATA USING MACHINE LEARNING MODELS | MANEJWALA, ISMAIL A | 3628 | §101 | Non-Final OA | — | Pending | Oct 31, 2023 |
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