Technology area: Transportation, E-Commerce & Mechanical Systems
3 pending office actions • 1 art units • 3 examiners • 0 of 3 (0%) have an AI response strategy ready
Aetech Corporation is managing 3 pending office actions within the Transportation, E-Commerce & Mechanical Systems technology area. Each of these 3 actions is assigned to a different person, resulting in 3 distinct examiners for the portfolio. All 3 actions are located within 1 distinct art unit, showing a high degree of technical concentration at the group level.
GARCIA, PAULO ANDRES is the busiest examiner for the company, currently responsible for 1 pending office action. This indicates that while the company's applications are concentrated in a single art unit, they are being reviewed by 3 different individuals within that group. Because there are 3 actions and 3 distinct examiners, no single examiner has a dominant influence over the portfolio. The company must manage its prosecution strategy to account for the individual perspectives of 3 different examiners even though all matters are being handled within the same art unit.
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 |
|---|---|
| §103 only | 1 (33%) |
| Multi-statute (no §101) | 2 (67%) |
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 |
|---|---|---|---|
| ORANGE, DAVID BENJAMIN | 1 | 32.1% | +28.8% |
| GARCIA, PAULO ANDRES | 1 | 80.4% | +25.1% |
| KUMAR, KALYANAVENKA K | 1 | 72.9% | +18.3% |
Cases in front of an examiner with an allow rate of 80%+ where the difficulty is Easy or Medium. The top 1 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18880321 | HYPERSPECTRAL IMAGE-BASED WASTE MATERIAL DISCRIMINATION SYSTEM | GARCIA, PAULO ANDRES | — |
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 |
|---|---|---|---|
| 18880323 | WASTE CLASSIFICATION SYSTEM BASED ON VISION-HYPERSPECTRAL FUSION DATA | ORANGE, DAVID BENJAMIN | — |
| 18869551 | WASTE SORTING SYSTEM CONSIDERING THE CHARACTERISTICS OF EACH WASTE DISPOSAL FACILITY | KUMAR, KALYANAVENKA K | — |
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 3 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18880323 | WASTE CLASSIFICATION SYSTEM BASED ON VISION-HYPERSPECTRAL FUSION DATA | ORANGE, DAVID BENJAMIN | — |
| 18880321 | HYPERSPECTRAL IMAGE-BASED WASTE MATERIAL DISCRIMINATION SYSTEM | GARCIA, PAULO ANDRES | — |
| 18869551 | WASTE SORTING SYSTEM CONSIDERING THE CHARACTERISTICS OF EACH WASTE DISPOSAL FACILITY | KUMAR, KALYANAVENKA K | — |
| Art Unit | Apps |
|---|---|
| 3653 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18880323 | WASTE CLASSIFICATION SYSTEM BASED ON VISION-HYPERSPECTRAL FUSION DATA | ORANGE, DAVID BENJAMIN | — | §102§103§112Other | Non-Final OA | — | Pending | Dec 31, 2024 |
| 18880321 | HYPERSPECTRAL IMAGE-BASED WASTE MATERIAL DISCRIMINATION SYSTEM | GARCIA, PAULO ANDRES | — | §103Other | Non-Final OA | — | Pending | Dec 31, 2024 |
| 18869551 | WASTE SORTING SYSTEM CONSIDERING THE CHARACTERISTICS OF EACH WASTE DISPOSAL FACILITY | KUMAR, KALYANAVENKA K | 3653 | §102§112 | Non-Final OA | — | Pending | Nov 26, 2024 |
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