Prosecution Insights
Prosecution Insights
1 pending office actions • 0 art units • 1 examiners • 0 of 1 (0%) have an AI response strategy ready
Attained AI Oü currently has 1 pending office action. This action is assigned to 1 distinct examiner, WU, NICHOLAS S. The portfolio currently lists 0 distinct art units, reflecting the administrative status of the pending matter. This single pending action represents the entirety of the company's active office action workload at this time, indicating a highly focused prosecution phase.
WU, NICHOLAS S is the busiest examiner, overseeing 1 pending office action. Since there is only 1 distinct examiner, this individual is responsible for the company's active prosecution. This one-to-one relationship between the examiner and the pending action allows for a direct line of communication. The presence of 0 distinct art units simplifies the organizational overhead for the practitioner. Because WU, NICHOLAS S is responsible for the 1 pending office action, the prosecution strategy can be entirely tailored to this examiner's specific feedback. This centralized structure ensures that all current efforts are directed toward resolving the single matter at hand.
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 |
|---|---|---|---|
| WU, NICHOLAS S | 1 | 52.4% | +31.4% |
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 |
|---|---|---|---|
| 18401999 | METHOD OF CONSTRUCTING LONG AND SHORT-RANGE DEPENDENCY NETWORK LEARNING MODEL, AND CLASSIFYING HEART RATE SOUND DATA | WU, NICHOLAS S | — |
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 |
|---|---|---|---|
| 18401999 | METHOD OF CONSTRUCTING LONG AND SHORT-RANGE DEPENDENCY NETWORK LEARNING MODEL, AND CLASSIFYING HEART RATE SOUND DATA | WU, NICHOLAS S | — |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18401999 | METHOD OF CONSTRUCTING LONG AND SHORT-RANGE DEPENDENCY NETWORK LEARNING MODEL, AND CLASSIFYING HEART RATE SOUND DATA | WU, NICHOLAS S | — | §101§103§112 | Non-Final OA | — | Pending | Jan 02, 2024 |
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