Prosecution Insights
Prosecution Insights
Technology area: Transportation, E-Commerce & Mechanical Systems
1 pending office actions • 1 art units • 1 examiners • 0 of 1 (0%) have an AI response strategy ready
Samya AI Technologies Private Limited maintains 1 pending office action in the Transportation, E-Commerce & Mechanical Systems technology area. This workload is currently assigned to 1 distinct examiner and 1 distinct art unit. Such a concentrated prosecution profile indicates that the company's current legal efforts are focused on a singular technical advancement. This lack of examiner diversity means that the outcome of the entire pending portfolio rests on a single point of success within the USPTO.
The busiest examiner, MITCHELL, NATHAN A, is responsible for 1 busiest examiner pending office action. Since there is only 1 pending office action in total, this examiner possesses complete oversight of the company's active applications. Practitioners must prioritize understanding the specific examination style of MITCHELL, NATHAN A, as there are no other examiners involved to provide a baseline for comparison or a different perspective on the Transportation, E-Commerce & Mechanical Systems claims.
With 1 distinct art unit involved, the administrative complexity is minimized, yet the stakes for this single matter are high. The prosecution strategy should be deeply informed by the art unit's specific trends. Because the company has only 1 pending office action, every response filed is a critical step in maintaining the momentum of the portfolio. The 1 distinct examiner and 1 distinct art unit represent the total administrative footprint for the current cycle.
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 + 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 |
|---|---|---|---|
| MITCHELL, NATHAN A | 1 | 73.0% | +10.0% |
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 |
|---|---|---|---|
| 17837004 | SYSTEM AND METHOD FOR ESTIMATING METRIC FORECASTS ASSOCIATED WITH RELATED ENTITIES WITH MORE ACCURACY BY USING A METRIC FORECAST ENTITY RELATIONSHIP MACHINE LEARNING MODEL | MITCHELL, NATHAN A | 20d |
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 |
|---|---|---|---|
| 17837004 | SYSTEM AND METHOD FOR ESTIMATING METRIC FORECASTS ASSOCIATED WITH RELATED ENTITIES WITH MORE ACCURACY BY USING A METRIC FORECAST ENTITY RELATIONSHIP MACHINE LEARNING MODEL | MITCHELL, NATHAN A | 20d |
| Art Unit | Apps |
|---|---|
| 3627 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 17837004 | SYSTEM AND METHOD FOR ESTIMATING METRIC FORECASTS ASSOCIATED WITH RELATED ENTITIES WITH MORE ACCURACY BY USING A METRIC FORECAST ENTITY RELATIONSHIP MACHINE LEARNING MODEL | MITCHELL, NATHAN A | 3627 | §101§112 | Final Rejection | 20d | Pending | Jun 09, 2022 |
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