Technology areas: Computing & Software • Communications • Transportation, E-Commerce & Mechanical Systems
14 pending office actions • 12 art units • 14 examiners • 0 of 14 (0%) have an AI response strategy ready • 30 patents granted in the last 365 days
Autobrains Technologies Ltd. has 14 pending office actions in Transportation, E-Commerce & Mechanical Systems. The matters involve 14 distinct examiners and 14 distinct art units, indicating a fully distributed examination profile. No single examiner or art unit provides a central point for portfolio-wide prosecution management.
REFAI, RAMSEY is the busiest examiner with 1 pending matter. Counsel should therefore rely on centralized tracking and a shared technical framework, while allowing each response to address the particular prior art, claim interpretation, and procedural posture identified in its action.
The broad assignment pattern makes consistency especially important for related disclosures and claim terminology. It also means that lessons from one response may be useful as drafting guidance, but cannot be assumed to control the treatment of another application.
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 + other | 6 (43%) |
| §103 only | 3 (21%) |
| §112 only | 1 (7%) |
| Double-patenting + other | 1 (7%) |
| Multi-statute (no §101) | 3 (21%) |
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 |
|---|---|---|---|
| REFAI, RAMSEY | 1 | 50.7% | +12.6% |
| JONES, ANDREW B | 1 | 71.7% | +24.3% |
| SITTNER, MATTHEW T | 1 | 57.9% | +56.1% |
| COUSO, JOSE L | 1 | 90.2% | +8.4% |
| MCCLEARY, CAITLIN RENEE | 1 | 59.7% | +26.5% |
| SHIMELES, BEZAWIT NOLAWI | 1 | 90.0% | +0.0% |
| SMITH, JORDAN T | 1 | 67.0% | +9.0% |
| KUDO, KEN | 1 | — | — |
| SHALU, ZELALEM W | 1 | 31.9% | +21.7% |
| DUONG, HIEN LUONGVAN | 1 | 75.0% | +23.3% |
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 |
|---|---|---|---|
| 18800477 | LEARNING BY PREDICTION THROUGH IMAGE LEVEL REPRESENTATION | COUSO, JOSE L | — |
| 18651522 | DYNAMIC CLASSIFICATION FOR AUTONOMOUS DRIVING | SHIMELES, BEZAWIT NOLAWI | — |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 8 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18595381 | TRAVEL LANE ELEMENT CLASSIFICATION | KUDO, KEN | 23d |
| 18896906 | REAL TIME AIR PERCEPTION | REFAI, RAMSEY | — |
| 18824937 | DECORRELATED TOPIC BASED REPRESENTATION OF ROAD ELEMENTS FOR CLASSIFICATION | JONES, ANDREW B | — |
| 18822285 | PIXEL BASED WITH OBJECT BASED DECISION MAKING APPROACH FOR DRIVING | SITTNER, MATTHEW T | — |
| 18627440 | USING SENSED INFORMATION FROM DIFFERENT TYPES OF SENSORS | SMITH, JORDAN T | — |
| 18522910 | SYSTEM AND METHOD OF CREATING INTERPRETABLE LATENT REPRESENTATIONS OF AN ARTIFICIAL INTELLIGENCE MODEL | DUONG, HIEN LUONGVAN | — |
| 18466793 | Accuracy of Object Detection | HO, MATTHEW | — |
| 18451118 | METHOD FOR REDUCING COMPUTATIONAL COST FOR AUTONOMOUS DRIVING SYSTEM | ASEGDEW, NATNAEL AREGA | — |
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 6 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18896906 | REAL TIME AIR PERCEPTION | REFAI, RAMSEY | — |
| 18824937 | DECORRELATED TOPIC BASED REPRESENTATION OF ROAD ELEMENTS FOR CLASSIFICATION | JONES, ANDREW B | — |
| 18822285 | PIXEL BASED WITH OBJECT BASED DECISION MAKING APPROACH FOR DRIVING | SITTNER, MATTHEW T | — |
| 18800751 | SELECTIVE LEARNING BY PREDICTION FOR DRIVING | MCCLEARY, CAITLIN RENEE | — |
| 18405500 | OVERCOMING TECHNICAL CHALLANGES OF WORKING IN A VERY HIGH DIMENSIONAL SPACE | SHALU, ZELALEM W | — |
| 18522910 | SYSTEM AND METHOD OF CREATING INTERPRETABLE LATENT REPRESENTATIONS OF AN ARTIFICIAL INTELLIGENCE MODEL | DUONG, HIEN LUONGVAN | — |
| Art Unit | Apps |
|---|---|
| 2667 | 2 |
| 3669 | 2 |
| 3664 | 1 |
| 3629 | 1 |
| 2673 | 1 |
| 3666 | 1 |
| 2671 | 1 |
| 2145 | 1 |
| 2147 | 1 |
| 2122 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18896906 | REAL TIME AIR PERCEPTION | REFAI, RAMSEY | 3664 | §102§103§112 | Final Rejection | — | Pending | Sep 26, 2024 |
| 18824937 | DECORRELATED TOPIC BASED REPRESENTATION OF ROAD ELEMENTS FOR CLASSIFICATION | JONES, ANDREW B | 2667 | §101§102§112 | Final Rejection | — | Pending | Sep 05, 2024 |
| 18822285 | PIXEL BASED WITH OBJECT BASED DECISION MAKING APPROACH FOR DRIVING | SITTNER, MATTHEW T | 3629 | §101§103§112 | Non-Final OA | — | Pending | Sep 02, 2024 |
| 18800477 | LEARNING BY PREDICTION THROUGH IMAGE LEVEL REPRESENTATION | COUSO, JOSE L | 2667 | §102DP | Non-Final OA | — | Pending | Aug 12, 2024 |
| 18800751 | SELECTIVE LEARNING BY PREDICTION FOR DRIVING | MCCLEARY, CAITLIN RENEE | 3669 | §103 | Non-Final OA | — | Pending | Aug 12, 2024 |
| 18651522 | DYNAMIC CLASSIFICATION FOR AUTONOMOUS DRIVING | SHIMELES, BEZAWIT NOLAWI | 2673 | §103 | Final Rejection | — | Pending | Apr 30, 2024 |
| 18627440 | USING SENSED INFORMATION FROM DIFFERENT TYPES OF SENSORS | SMITH, JORDAN T | 3666 | §101§103 | Non-Final OA | — | Pending | Apr 04, 2024 |
| 18595381 | TRAVEL LANE ELEMENT CLASSIFICATION | KUDO, KEN | 2671 | §103§112 | Final Rejection | 23d | Pending | Mar 04, 2024 |
| 18405500 | OVERCOMING TECHNICAL CHALLANGES OF WORKING IN A VERY HIGH DIMENSIONAL SPACE | SHALU, ZELALEM W | 2145 | §103 | Non-Final OA | — | Pending | Jan 05, 2024 |
| 18522910 | SYSTEM AND METHOD OF CREATING INTERPRETABLE LATENT REPRESENTATIONS OF AN ARTIFICIAL INTELLIGENCE MODEL | DUONG, HIEN LUONGVAN | 2147 | §101§103 | Non-Final OA | — | Pending | Nov 29, 2023 |
| 18466793 | Accuracy of Object Detection | HO, MATTHEW | 3669 | §101§102§103§112 | Non-Final OA | — | Pending | Sep 13, 2023 |
| 18451118 | METHOD FOR REDUCING COMPUTATIONAL COST FOR AUTONOMOUS DRIVING SYSTEM | ASEGDEW, NATNAEL AREGA | 2122 | §101§103 | Final Rejection | — | Pending | Aug 17, 2023 |
| 18355324 | DRIVING RELATED AUGMENTED VIRTUAL FIELDS | ARTIMEZ, DANA FERREN | 3667 | §112 | Non-Final OA | — | Pending | Jul 19, 2023 |
| 18327865 | PASSIVE READOUT | KIM, DAVID | 2141 | §103§112 | Final Rejection | — | Pending | Jun 01, 2023 |
IP Author helps IP teams respond to office actions faster with AI-generated responses, examiner analytics, and prosecution intelligence.
Start Free TrialAutobrains Technologies Ltd. has 14 pending office actions as of October 2026, spread across 12 art units and 14 examiners.
Ramsey Refai has the most, with 1 of Autobrains Technologies Ltd.'s pending office actions.
Mostly Transportation, E-Commerce & Mechanical Systems (USPTO Tech Center 3600), based on where its pending office actions are examined.
