Prosecution Insights
Prosecution Insights
Technology area: Transportation, E-Commerce & Mechanical Systems
6 pending office actions • 4 art units • 6 examiners • 0 of 6 (0%) have an AI response strategy ready • 4 patents granted in the last 365 days
American Airlines Inc. currently manages a company patent portfolio with 5 pending office actions. These matters are distributed across 3 distinct art units within the Transportation, E-Commerce & Mechanical Systems technology area. The prosecution work involves 5 distinct examiners, indicating a ratio of 1 examiner to each pending action across the portfolio. This distribution suggests that the company's legal strategy does not currently result in a concentration of matters under any single examiner's review.
ROBINSON, AKIBA KANELLE is identified as the busiest examiner for this portfolio. This specific examiner is responsible for 1 pending office action. The distribution of 5 pending actions among 3 art units suggests a concentrated focus within the broader technology area. Practitioners should note the diversity of examiners relative to the total volume of active matters, which may lead to varying prosecution timelines across the portfolio. The presence of 5 distinct examiners for 5 actions ensures that no individual examiner is disproportionately influenced by the company's broader filing activities.
Based on the USPTO statutory response window for each pending office action. 3 of the docket's apps have a known mailing date; the rest are excluded from the tile counts.
Every pending office action with a known statutory deadline, placed on a days-until-due axis. Dots left of Today are overdue; the further right, the more runway. Cases that share a deadline window stack vertically. 3 of the docket's apps have a known mailing date.
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 | 3 (50%) |
| §101 + other | 3 (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 |
|---|---|---|---|
| ROBINSON, AKIBA KANELLE | 1 | 38.2% | +24.6% |
| MOLNAR, HUNTER A | 1 | 50.6% | +33.1% |
| STIVALETTI, MATHEUS R | 1 | 37.1% | +28.3% |
| BROWN, SARA GRACE | 1 | 29.2% | +33.2% |
| CHOY, PAN G | 1 | 24.4% | +34.9% |
| ZEROUAL, OMAR | 1 | 33.5% | +39.7% |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 6 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18789330 | COMPUTER-BASED SYSTEMS AND METHODS FOR AUTOMATED AIRCRAFT CARGO LOAD PLANNING AND OPTIMAL SHIPPING CONFIGURATIONS | MOLNAR, HUNTER A | 8d overdue |
| 17971272 | RESOURCE ASSIGNMENTS BASED ON STATION CONSTRAINTS | CHOY, PAN G | 23d |
| 16854673 | UNOBSCURING ALGORITHM | ZEROUAL, OMAR | 40d |
| 19204369 | FARE CLASSES WITH OBSCURED DEMAND OR UNCONSTRAINED DEMAND | ROBINSON, AKIBA KANELLE | — |
| 18535828 | APPLYING LOGISTIC REGRESSION TO HISTORICAL DATA TO GENERATE FORECAST COEFFICIENTS | STIVALETTI, MATHEUS R | — |
| 18481574 | SYSTEM AND METHOD FOR MANAGING DISRUPTIONS WITHIN A TRANSPORTATION SYSTEM USING DELAYS AND CANCELLATIONS OF TRAVEL LEGS | BROWN, SARA GRACE | — |
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 6 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18789330 | COMPUTER-BASED SYSTEMS AND METHODS FOR AUTOMATED AIRCRAFT CARGO LOAD PLANNING AND OPTIMAL SHIPPING CONFIGURATIONS | MOLNAR, HUNTER A | 8d overdue |
| 17971272 | RESOURCE ASSIGNMENTS BASED ON STATION CONSTRAINTS | CHOY, PAN G | 23d |
| 16854673 | UNOBSCURING ALGORITHM | ZEROUAL, OMAR | 40d |
| 19204369 | FARE CLASSES WITH OBSCURED DEMAND OR UNCONSTRAINED DEMAND | ROBINSON, AKIBA KANELLE | — |
| 18535828 | APPLYING LOGISTIC REGRESSION TO HISTORICAL DATA TO GENERATE FORECAST COEFFICIENTS | STIVALETTI, MATHEUS R | — |
| 18481574 | SYSTEM AND METHOD FOR MANAGING DISRUPTIONS WITHIN A TRANSPORTATION SYSTEM USING DELAYS AND CANCELLATIONS OF TRAVEL LEGS | BROWN, SARA GRACE | — |
| Art Unit | Apps |
|---|---|
| 3628 | 2 |
| 3623 | 1 |
| 3625 | 1 |
| 3624 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 19204369 | FARE CLASSES WITH OBSCURED DEMAND OR UNCONSTRAINED DEMAND | ROBINSON, AKIBA KANELLE | — | §101§102§103 | Final Rejection | — | Pending | May 09, 2025 |
| 18789330 | COMPUTER-BASED SYSTEMS AND METHODS FOR AUTOMATED AIRCRAFT CARGO LOAD PLANNING AND OPTIMAL SHIPPING CONFIGURATIONS | MOLNAR, HUNTER A | 3628 | §101§103 | Final Rejection | 8d overdue | Pending | Jul 30, 2024 |
| 18535828 | APPLYING LOGISTIC REGRESSION TO HISTORICAL DATA TO GENERATE FORECAST COEFFICIENTS | STIVALETTI, MATHEUS R | 3623 | §101 | Non-Final OA | — | Pending | Dec 11, 2023 |
| 18481574 | SYSTEM AND METHOD FOR MANAGING DISRUPTIONS WITHIN A TRANSPORTATION SYSTEM USING DELAYS AND CANCELLATIONS OF TRAVEL LEGS | BROWN, SARA GRACE | 3625 | §101 | Final Rejection | — | Pending | Oct 05, 2023 |
| 17971272 | RESOURCE ASSIGNMENTS BASED ON STATION CONSTRAINTS | CHOY, PAN G | 3624 | §101 | Non-Final OA | 23d | Pending | Oct 21, 2022 |
| 16854673 | UNOBSCURING ALGORITHM | ZEROUAL, OMAR | 3628 | §101§112 | Final Rejection | 40d | Pending | Apr 21, 2020 |
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