Prosecution Insights
Prosecution Insights
3 pending office actions • 0 art units • 3 examiners • 0 of 3 (0%) have an AI response strategy ready • 4 patents granted in the last 365 days
Direct Cursus Technology L L C has 4 pending office actions within the Transportation, E-Commerce & Mechanical Systems technology area. These actions are being handled by 4 distinct examiners, which shows that each pending matter is under the review of a different individual. Despite this variety in examiners, all 4 pending actions are concentrated within 1 distinct art unit. This indicates a consistent technological focus for the company's current filings.
LEE, MICHAEL CHRISTOPHER is the busiest examiner for the portfolio, with 1 pending office action. Given that there are 4 pending office actions and 4 distinct examiners, the workload is distributed across the examiner pool. The concentration of all matters into 1 distinct art unit suggests that while the company interacts with several examiners, the technological focus of these applications is localized within a single office division. Practitioners should note that while examiner perspectives vary, the art unit's internal policies will likely remain consistent.
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 (33%) |
| §101 + other | 1 (33%) |
| Multi-statute (no §101) | 1 (33%) |
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 |
|---|---|---|---|
| LEE, MICHAEL CHRISTOPHER | 1 | 62.5% | +25.1% |
| MINOR, AYANNA YVETTE | 1 | 18.8% | +23.0% |
| SIPPEL, MOLLY CLARKE | 1 | 50.0% | +25.7% |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 3 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18669758 | METHOD AND A SYSTEM FOR TRAINING A CHATBOT SYSTEM | LEE, MICHAEL CHRISTOPHER | — |
| 18394988 | SYSTEM AND A METHOD OF GENERATING A TRAINING SET OF DATA FOR TRAINING A MACHINE-LEARNING ALGORITHM | MINOR, AYANNA YVETTE | — |
| 18395024 | METHODS AND SYSTEMS FOR TRAINING A DECISION-TREE BASED MACHINE LEARNING ALGORITHM (MLA) | SIPPEL, MOLLY CLARKE | — |
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 |
|---|---|---|---|
| 18669758 | METHOD AND A SYSTEM FOR TRAINING A CHATBOT SYSTEM | LEE, MICHAEL CHRISTOPHER | — |
| 18394988 | SYSTEM AND A METHOD OF GENERATING A TRAINING SET OF DATA FOR TRAINING A MACHINE-LEARNING ALGORITHM | MINOR, AYANNA YVETTE | — |
| 18395024 | METHODS AND SYSTEMS FOR TRAINING A DECISION-TREE BASED MACHINE LEARNING ALGORITHM (MLA) | SIPPEL, MOLLY CLARKE | — |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18669758 | METHOD AND A SYSTEM FOR TRAINING A CHATBOT SYSTEM | LEE, MICHAEL CHRISTOPHER | — | §103§112 | Non-Final OA | — | Pending | May 21, 2024 |
| 18394988 | SYSTEM AND A METHOD OF GENERATING A TRAINING SET OF DATA FOR TRAINING A MACHINE-LEARNING ALGORITHM | MINOR, AYANNA YVETTE | — | §101 | Non-Final OA | — | Pending | Dec 22, 2023 |
| 18395024 | METHODS AND SYSTEMS FOR TRAINING A DECISION-TREE BASED MACHINE LEARNING ALGORITHM (MLA) | SIPPEL, MOLLY CLARKE | — | §101§112 | Non-Final OA | — | Pending | Dec 22, 2023 |
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