Prosecution Insights
Prosecution Insights
2 pending office actions • 0 art units • 2 examiners • 0 of 2 (0%) have an AI response strategy ready • 2 patents granted in the last 365 days
Craif Inc. is currently navigating 2 pending office actions at the USPTO. These actions are split between 2 distinct examiners, ensuring that no single individual oversees the entirety of the pending portfolio. MESFIN, MATTHEWOS is identified as the busiest examiner, though they are currently responsible for only 1 pending action.
This distribution across those examiners suggests a diversified examination process for the matters. Because MESFIN, MATTHEWOS holds 1 pending action, the workload is evenly balanced among the examiners involved. Practitioners can expect individualized feedback from each of the examiners as these applications progress through the USPTO.
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 (50%) |
| Multi-statute (no §101) | 1 (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 |
|---|---|---|---|
| MESFIN, MATTHEWOS | 1 | — | — |
| SABOUR, GHAZAL | 1 | 37.8% | +43.2% |
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 |
|---|---|---|---|
| 18685689 | NEURAL-NETWORK-BASED CLASSIFIER | MESFIN, MATTHEWOS | — |
| 18248781 | METHOD FOR EVALUATING LIKELIHOOD OF OBSERVATION VALUE AND PROGRAM | SABOUR, GHAZAL | — |
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 |
|---|---|---|---|
| 18248781 | METHOD FOR EVALUATING LIKELIHOOD OF OBSERVATION VALUE AND PROGRAM | SABOUR, GHAZAL | — |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18685689 | NEURAL-NETWORK-BASED CLASSIFIER | MESFIN, MATTHEWOS | — | §102§103 | Non-Final OA | — | Pending | Feb 22, 2024 |
| 18248781 | METHOD FOR EVALUATING LIKELIHOOD OF OBSERVATION VALUE AND PROGRAM | SABOUR, GHAZAL | — | §101§103§112 | Non-Final OA | — | Pending | Apr 12, 2023 |
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