Prosecution Insights
Prosecution Insights
Technology area: Networking & Security
8 pending office actions • 5 art units • 8 examiners • 0 of 8 (0%) have an AI response strategy ready • 5 patents granted in the last 365 days
Sandpiper Cdn LLC manages a company patent portfolio containing 8 pending office actions. These actions are categorized under the Networking & Security technology area. The portfolio demonstrates significant breadth, with matters distributed across 5 distinct art units. This variety of art units suggests that the company's networking technologies span several specialized technical classifications within the patent office.
The prosecution effort involves 8 distinct examiners, which equals the total number of 8 pending office actions. JACOBS-BURTON, LASHONDA T is the busiest examiner for the portfolio, currently overseeing 1 pending office action. This indicates a highly distributed workload where every pending matter is assigned to a different individual. For a practitioner, this means that prosecution strategies must be tailored to 8 different examiner preferences. The use of 5 distinct art units for 8 actions further emphasizes the need for a versatile approach to the company's diverse technical filings in the networking and security space.
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 |
|---|---|
| §103 only | 4 (50%) |
| Double-patenting only | 1 (12%) |
| Multi-statute (no §101) | 3 (38%) |
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 |
|---|---|---|---|
| JACOBS-BURTON, LASHONDA T | 1 | 91.3% | -12.9% |
| KASSA, ELIZABETH | 1 | 80.2% | -5.5% |
| TODD, GREGORY G | 1 | 38.6% | -2.7% |
| RAZA, MUHAMMAD A | 1 | 56.1% | +68.7% |
| CHANG, TOM Y | 1 | 53.4% | +20.0% |
| FIORILLO, JAMES N | 1 | 85.7% | +37.1% |
| ALGIBHAH, HAMZA N | 1 | 79.1% | +3.3% |
| BAROT, BHARAT | 1 | 87.4% | +8.1% |
Cases in front of an examiner with an allow rate of 80%+ where the difficulty is Easy or Medium. The top 3 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 19204205 | NETWORK ADDRESS RESOLUTION | JACOBS-BURTON, LASHONDA T | — |
| 18805934 | TIME AND LOCATION-BASED TREND PREDICTION IN A CONTENT DELIVERY NETWORK (CDN) | FIORILLO, JAMES N | — |
| 18772505 | REQUEST PROCESSING IN A CONTENT DELIVERY FRAMEWORK | BAROT, BHARAT | — |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 3 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 19182172 | PACKET PROCESSING OF STREAMING CONTENT IN A COMMUNICATIONS NETWORK | KASSA, ELIZABETH | — |
| 18961965 | ARTIFICIAL INTELLIGENCE LOG PROCESSING AND CONTENT DISTRIBUTION NETWORK OPTIMIZATION | TODD, GREGORY G | — |
| 18824604 | SYSTEM AND METHOD FOR IMPROVEMENTS TO A CONTENT DELIVERY NETWORK | CHANG, TOM Y | — |
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 |
|---|---|---|---|
| 18898151 | FRONT-END OPTIMIZATION IN A CONTENT DELIVERY NETWORK (CDN) | RAZA, MUHAMMAD A | — |
| 18824604 | SYSTEM AND METHOD FOR IMPROVEMENTS TO A CONTENT DELIVERY NETWORK | CHANG, TOM Y | — |
| 18805934 | TIME AND LOCATION-BASED TREND PREDICTION IN A CONTENT DELIVERY NETWORK (CDN) | FIORILLO, JAMES N | — |
| Art Unit | Apps |
|---|---|
| 2449 | 1 |
| 2455 | 1 |
| 2444 | 1 |
| 2441 | 1 |
| 2453 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 19204205 | NETWORK ADDRESS RESOLUTION | JACOBS-BURTON, LASHONDA T | — | DP | Non-Final OA | — | Pending | May 09, 2025 |
| 19182172 | PACKET PROCESSING OF STREAMING CONTENT IN A COMMUNICATIONS NETWORK | KASSA, ELIZABETH | — | §103§112Other | Non-Final OA | — | Pending | Apr 17, 2025 |
| 18961965 | ARTIFICIAL INTELLIGENCE LOG PROCESSING AND CONTENT DISTRIBUTION NETWORK OPTIMIZATION | TODD, GREGORY G | — | §103§112 | Non-Final OA | — | Pending | Nov 27, 2024 |
| 18898151 | FRONT-END OPTIMIZATION IN A CONTENT DELIVERY NETWORK (CDN) | RAZA, MUHAMMAD A | 2449 | §103Other | Final Rejection | — | Pending | Sep 26, 2024 |
| 18824604 | SYSTEM AND METHOD FOR IMPROVEMENTS TO A CONTENT DELIVERY NETWORK | CHANG, TOM Y | 2455 | §102§103Other | Non-Final OA | — | Pending | Sep 04, 2024 |
| 18805934 | TIME AND LOCATION-BASED TREND PREDICTION IN A CONTENT DELIVERY NETWORK (CDN) | FIORILLO, JAMES N | 2444 | §103 | Final Rejection | — | Pending | Aug 15, 2024 |
| 18786086 | SYSTEMS AND METHODS FOR CONTENT SERVER RENDEZVOUS IN A DUAL STACK PROTOCOL NETWORK | ALGIBHAH, HAMZA N | 2441 | §103 | Final Rejection | 41d | Pending | Jul 26, 2024 |
| 18772505 | REQUEST PROCESSING IN A CONTENT DELIVERY FRAMEWORK | BAROT, BHARAT | 2453 | §103 | Final Rejection | — | Pending | Jul 15, 2024 |
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