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
Midl currently maintains 1 pending office action in the Transportation, E-Commerce & Mechanical Systems technology area. This matter is assigned to 1 distinct examiner within 1 distinct art unit. The prosecution activity is currently limited to this 1 point of interaction, suggesting a very specific or early-stage patent strategy. This concentration means that all current prosecution efforts are focused on a single technical and administrative track.
MITCHELL, NATHAN A is the busiest examiner with 1 pending office action. With only 1 active matter, the company's prosecution strategy is defined by the specific requirements of this 1 examiner. There is no broader portfolio activity to provide context or alternative paths for the company's current intellectual property efforts. Practitioners must rely solely on the feedback from this 1 examiner to guide the prosecution of the company's pending application, as no other data points are available within the current portfolio.
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 (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 | 72.9% | +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 |
|---|---|---|---|
| 19074473 | MACHINE LEARNING METHOD FOR LOGISTICS AUTOMATION | MITCHELL, NATHAN 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 |
|---|---|---|---|
| 19074473 | MACHINE LEARNING METHOD FOR LOGISTICS AUTOMATION | MITCHELL, NATHAN A | — |
| Art Unit | Apps |
|---|---|
| 3627 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 19074473 | MACHINE LEARNING METHOD FOR LOGISTICS AUTOMATION | MITCHELL, NATHAN A | 3627 | §101 | Non-Final OA | — | Pending | Mar 10, 2025 |
IP Author helps IP teams respond to office actions faster with AI-generated responses, examiner analytics, and prosecution intelligence.
Start Free TrialMidl has 1 pending office actions as of October 2026, spread across 1 art units and 1 examiners.
Nathan A Mitchell has the most, with 1 of Midl's pending office actions.
Mostly Transportation, E-Commerce & Mechanical Systems (USPTO Tech Center 3600), based on where its pending office actions are examined.
