Prosecution Insights
Prosecution Insights
Technology areas: Computing & Software • Transportation, E-Commerce & Mechanical Systems
9 pending office actions • 4 art units • 9 examiners • 0 of 9 (0%) have an AI response strategy ready • 9 patents granted in the last 365 days
Multiverse Computing S L maintains a portfolio in the Computing & Software technology area with 10 pending office actions. These matters are spread across an equal number of 10 distinct examiners. This distribution of actions among the examiners suggests a lack of examiner-specific concentration in the current workload, requiring the company to manage many separate examiner relationships simultaneously. Such a broad distribution can lead to varied prosecution experiences as each examiner applies their own interpretation of patent law and office guidelines to the pending office actions.
The portfolio spans 5 distinct art units, showing a technical footprint within the software sector. HICKS, AUSTIN JAMES is identified as the busiest examiner, though he only accounts for 1 pending office action. Because every examiner in the portfolio currently handles exactly the same amount of work, the workload is spread across the distinct examiners involved. With the office actions across 5 distinct art units, the company faces a diverse set of technical reviews that require specialized expertise for each 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 only | 3 (33%) |
| §101 + other | 2 (22%) |
| §103 only | 2 (22%) |
| Multi-statute (no §101) | 1 (11%) |
| No statute on record | 1 (11%) |
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 |
|---|---|---|---|
| HICKS, AUSTIN JAMES | 1 | 75.0% | +25.8% |
| GARNER, CASEY R | 1 | 71.5% | +15.9% |
| DINH, PAUL | 1 | 89.5% | +4.2% |
| MRABI, HASSAN | 1 | 78.0% | +33.3% |
| KHAN, SHAHID K | 1 | 74.6% | +15.3% |
| DO, AN H | 1 | 90.5% | +7.0% |
| PULLIAM, JOSEPH CONSTANTINE | 1 | 38.1% | +31.2% |
| MORICE DE VARGAS, SARA JESSICA | 1 | 8.8% | +22.1% |
| TRAN, AMY NMN | 1 | 38.2% | +37.0% |
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 |
|---|---|---|---|
| 17147142 | METHODS AND APPARATUSES FOR OPTIMAL DECISION WITH QUANTUM DEVICE | TRAN, AMY NMN | 53d overdue |
| 18399994 | Control with Scalable, Efficient Inference based on Non-Linear Tensor Networks | HICKS, AUSTIN JAMES | — |
| 18398883 | SYSTEM AND METHODS FOR IMPLEMENTING VARIATIONAL EQUIVARIANT QUANTUM CIRCUITS FOR QUANTUM MACHINE LEARNING AND RELATED METHODS | DINH, PAUL | — |
| 18374732 | Tensor Network-Enhanced Prime Factorization | DO, AN H | — |
| 18087779 | FERMIONIC TENSOR MACHINE LEARNING FOR QUANTUM CHEMISTRY | PULLIAM, JOSEPH CONSTANTINE | — |
| 17936974 | MONITORIZATION AND FORECAST OF PAIN AND ILLNESS IN PATIENTS WITH QUANTUM COMPUTING | MORICE DE VARGAS, SARA JESSICA | — |
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 7 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 17147142 | METHODS AND APPARATUSES FOR OPTIMAL DECISION WITH QUANTUM DEVICE | TRAN, AMY NMN | 53d overdue |
| 18399994 | Control with Scalable, Efficient Inference based on Non-Linear Tensor Networks | HICKS, AUSTIN JAMES | — |
| 18398879 | SYSTEM AND METHODS FOR IMPLEMENTING SYMMETRIC TENSOR NETWORKS FOR QUANTUM MACHINE LEARNING AND RELATED METHODS | GARNER, CASEY R | — |
| 18497513 | METHOD FOR ADJUSTING A BOOSTED CLASSIFIER, BOOSTED CLASSIFIER AND DEVICE OR SYSTEM FOR PERFORMING THE METHOD | MRABI, HASSAN | — |
| 18497536 | Method for Adjusting a Boosted Classifier, Boosted Classifier and Device or System for Performing the Method | KHAN, SHAHID K | — |
| 18087779 | FERMIONIC TENSOR MACHINE LEARNING FOR QUANTUM CHEMISTRY | PULLIAM, JOSEPH CONSTANTINE | — |
| 17936974 | MONITORIZATION AND FORECAST OF PAIN AND ILLNESS IN PATIENTS WITH QUANTUM COMPUTING | MORICE DE VARGAS, SARA JESSICA | — |
| Art Unit | Apps |
|---|---|
| 4100 | 2 |
| 2143 | 1 |
| 3681 | 1 |
| 2126 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18399994 | Control with Scalable, Efficient Inference based on Non-Linear Tensor Networks | HICKS, AUSTIN JAMES | — | §101§103 | Final Rejection | — | Pending | Dec 29, 2023 |
| 18398879 | SYSTEM AND METHODS FOR IMPLEMENTING SYMMETRIC TENSOR NETWORKS FOR QUANTUM MACHINE LEARNING AND RELATED METHODS | GARNER, CASEY R | — | §103 | Non-Final OA | — | Pending | Dec 28, 2023 |
| 18398883 | SYSTEM AND METHODS FOR IMPLEMENTING VARIATIONAL EQUIVARIANT QUANTUM CIRCUITS FOR QUANTUM MACHINE LEARNING AND RELATED METHODS | DINH, PAUL | — | §102§112 | Non-Final OA | — | Pending | Dec 28, 2023 |
| 18497513 | METHOD FOR ADJUSTING A BOOSTED CLASSIFIER, BOOSTED CLASSIFIER AND DEVICE OR SYSTEM FOR PERFORMING THE METHOD | MRABI, HASSAN | 4100 | — | Non-Final OA | — | Pending | Oct 30, 2023 |
| 18497536 | Method for Adjusting a Boosted Classifier, Boosted Classifier and Device or System for Performing the Method | KHAN, SHAHID K | 4100 | §103 | Non-Final OA | — | Pending | Oct 30, 2023 |
| 18374732 | Tensor Network-Enhanced Prime Factorization | DO, AN H | — | §101 | Non-Final OA | — | Pending | Sep 29, 2023 |
| 18087779 | FERMIONIC TENSOR MACHINE LEARNING FOR QUANTUM CHEMISTRY | PULLIAM, JOSEPH CONSTANTINE | 2143 | §101§103 | Non-Final OA | — | Pending | Dec 22, 2022 |
| 17936974 | MONITORIZATION AND FORECAST OF PAIN AND ILLNESS IN PATIENTS WITH QUANTUM COMPUTING | MORICE DE VARGAS, SARA JESSICA | 3681 | §101 | Final Rejection | — | Pending | Sep 30, 2022 |
| 17147142 | METHODS AND APPARATUSES FOR OPTIMAL DECISION WITH QUANTUM DEVICE | TRAN, AMY NMN | 2126 | §101 | Non-Final OA | 53d overdue | Pending | Jan 12, 2021 |
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