Prosecution Insights
Prosecution Insights
Technology area: Medical Devices & Mechanical Engineering
3 pending office actions • 1 art units • 3 examiners • 0 of 3 (0%) have an AI response strategy ready
Examroom AI Corp. currently manages 3 pending office actions within the Medical Devices & Mechanical Engineering technology area. These matters are distributed among 3 distinct examiners, indicating that each application is being reviewed by a different individual. The prosecution is organized across 1 distinct art unit, suggesting that the company's filings in the Medical Devices & Mechanical Engineering sector are grouped into a single technical category.
The busiest examiner for the portfolio is FRENCH, CORRELL T, who is responsible for 1 busiest examiner pending office action. This confirms that the workload is perfectly distributed, as each of the 3 distinct examiners is handling exactly one of the company's pending matters. No single examiner currently manages more than one of the 3 pending office actions in the Medical Devices & Mechanical Engineering sector.
The use of 1 distinct art unit for 3 pending office actions indicates a high degree of technical focus within the Medical Devices & Mechanical Engineering field. However, with 3 distinct examiners involved, the company must still account for a variety of examination styles. The presence of 3 distinct examiners for 3 pending office actions requires the company to maintain several simultaneous dialogues with the patent office while following the standards of 1 distinct art unit.
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 (33%) |
| §103 only | 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 |
|---|---|---|---|
| FRENCH, CORRELL T | 1 | 44.4% | +32.7% |
| ORTIZ SANCHEZ, MICHAEL | 1 | 67.1% | +27.2% |
| LEE, BENEDICT E | 1 | 87.6% | +13.4% |
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 |
|---|---|---|---|
| 19017917 | METHOD AND SYSTEM OF ADAPTIVE TESTING VIA CONTINUOUS REAL TIME SCORING | FRENCH, CORRELL T | 43d |
| 18971220 | METHOD AND SYSTEM FOR TRAINING AND DEPLOYMENT OF AI NEURAL NETWORK IN HUMAN ACTION SKILLS BASED EXAMINATIONS | LEE, BENEDICT E | — |
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 |
|---|---|---|---|
| 19017917 | METHOD AND SYSTEM OF ADAPTIVE TESTING VIA CONTINUOUS REAL TIME SCORING | FRENCH, CORRELL T | 43d |
| 18983508 | METHOD AND SYSTEM OF TRAINING AN AI NEURAL NETWORK IN DEPLOYMENT OF VOICE BASED AUTHENTICATION FOR A REMOTE EXAMINATION SETTING | ORTIZ SANCHEZ, MICHAEL | — |
| 18971220 | METHOD AND SYSTEM FOR TRAINING AND DEPLOYMENT OF AI NEURAL NETWORK IN HUMAN ACTION SKILLS BASED EXAMINATIONS | LEE, BENEDICT E | — |
| Art Unit | Apps |
|---|---|
| 3715 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 19017917 | METHOD AND SYSTEM OF ADAPTIVE TESTING VIA CONTINUOUS REAL TIME SCORING | FRENCH, CORRELL T | 3715 | §101§103§112 | Final Rejection | 43d | Pending | Jan 13, 2025 |
| 18983508 | METHOD AND SYSTEM OF TRAINING AN AI NEURAL NETWORK IN DEPLOYMENT OF VOICE BASED AUTHENTICATION FOR A REMOTE EXAMINATION SETTING | ORTIZ SANCHEZ, MICHAEL | — | §103 | Non-Final OA | — | Pending | Dec 17, 2024 |
| 18971220 | METHOD AND SYSTEM FOR TRAINING AND DEPLOYMENT OF AI NEURAL NETWORK IN HUMAN ACTION SKILLS BASED EXAMINATIONS | LEE, BENEDICT E | — | §102§103 | Non-Final OA | — | Pending | Dec 06, 2024 |
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