Prosecution Insights
Prosecution Insights
Technology area: Networking & Security
3 pending office actions • 1 art units • 3 examiners • 0 of 3 (0%) have an AI response strategy ready • 5 patents granted in the last 365 days
Ambiq Micro, Inc. currently has 3 pending office actions within the Networking & Security technology area. These actions are distributed across 3 distinct examiners, yet they are all contained within 1 distinct art unit. This suggests that while multiple examiners are reviewing the company's work, the subject matter remains consistent within a single administrative division of the patent office. This concentration in 1 distinct art unit can help the company maintain a unified prosecution strategy across different applications, as the examiners likely share similar internal guidelines.
CHERY, MARDOCHEE is the busiest examiner, holding 1 busiest examiner pending office action. With the pending office actions and 3 distinct examiners, the portfolio's workload is distributed among several reviewers within the 1 distinct art unit. For the practitioner, this distribution provides a unified environment for prosecution, even though interactions are required with multiple individual examiners. The total pending office actions count is 3, which requires careful attention to the individual preferences of each reviewer while adhering to the standards of the assigned art unit.
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 |
|---|---|
| §103 only | 1 (33%) |
| Double-patenting 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 |
|---|---|---|---|
| CHERY, MARDOCHEE | 1 | 88.5% | +10.3% |
| GRIJALVA LOBOS, BORIS D | 1 | 82.3% | +18.4% |
| RAHMAN, SM AZIZUR | 1 | 88.5% | +17.7% |
Cases in front of an examiner with an allow rate of 80%+ where the difficulty is Easy or Medium. The top 2 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 19232398 | ON-DEMAND ACTIVATION OF MEMORY PATH DURING SLEEP OR ACTIVE MODES | CHERY, MARDOCHEE | — |
| 18464500 | SCALABLE DISTRIBUTED NEURAL PROCESSING NETWORK | RAHMAN, SM AZIZUR | — |
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 |
|---|---|---|---|
| 19179593 | METHOD AND SYSTEM RECOVERY FROM UNEXPECTED MEMORY CORRUPTION ON A SYSTEM ON CHIP | GRIJALVA LOBOS, BORIS D | — |
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 |
|---|---|---|---|
| 19232398 | ON-DEMAND ACTIVATION OF MEMORY PATH DURING SLEEP OR ACTIVE MODES | CHERY, MARDOCHEE | — |
| 19179593 | METHOD AND SYSTEM RECOVERY FROM UNEXPECTED MEMORY CORRUPTION ON A SYSTEM ON CHIP | GRIJALVA LOBOS, BORIS D | — |
| 18464500 | SCALABLE DISTRIBUTED NEURAL PROCESSING NETWORK | RAHMAN, SM AZIZUR | — |
| Art Unit | Apps |
|---|---|
| 2434 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 19232398 | ON-DEMAND ACTIVATION OF MEMORY PATH DURING SLEEP OR ACTIVE MODES | CHERY, MARDOCHEE | — | DP | Non-Final OA | — | Pending | Jun 09, 2025 |
| 19179593 | METHOD AND SYSTEM RECOVERY FROM UNEXPECTED MEMORY CORRUPTION ON A SYSTEM ON CHIP | GRIJALVA LOBOS, BORIS D | — | §102§103§112 | Non-Final OA | — | Pending | Apr 15, 2025 |
| 18464500 | SCALABLE DISTRIBUTED NEURAL PROCESSING NETWORK | RAHMAN, SM AZIZUR | 2434 | §103 | Final Rejection | — | Pending | Sep 11, 2023 |
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