Prosecution Insights
Prosecution Insights
Technology area: Transportation, E-Commerce & Mechanical Systems
24 pending office actions • 10 art units • 20 examiners • 0 of 24 (0%) have an AI response strategy ready • 59 patents granted in the last 365 days
Maplebear Inc. (dba Instacart) maintains a patent portfolio centered on Transportation, E-Commerce & Mechanical Systems. The company currently faces 23 pending office actions, reflecting the volume of active prosecution. This workload is distributed across 9 distinct art units, which shows a technical footprint that spans multiple examination specialties.
The examination of these filings involves 19 distinct examiners, providing a range of perspectives on the company's applications. FRUNZI, VICTORIA E. is the busiest examiner for the portfolio, though she is responsible for 2 pending office actions. This distribution shows that no single examiner holds a dominant share of the 23 pending office actions.
Practitioners managing this portfolio must navigate a landscape involving 19 distinct examiners and 9 distinct art units. The fact that the active filings are spread across these units suggests that prosecution strategies may need to be tailored to the specific requirements of each group. The concentration of 2 pending office actions with the busiest examiner highlights the decentralized nature of the current workload. Success requires coordinating multiple parallel tracks across a broad range of examiner personalities.
Based on the USPTO statutory response window for each pending office action. 11 of the docket's apps have a known mailing date; the rest are excluded from the tile counts.
Every pending office action with a known statutory deadline, placed on a days-until-due axis. Dots left of Today are overdue; the further right, the more runway. Cases that share a deadline window stack vertically. 11 of the docket's apps have a known mailing date.
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 | 16 (67%) |
| §101 + other | 5 (21%) |
| §103 only | 2 (8%) |
| No statute on record | 1 (4%) |
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 |
|---|---|---|---|
| FRUNZI, VICTORIA E. | 2 | 25.4% | +24.4% |
| BAGGOT, BREFFNI | 2 | 35.3% | +25.8% |
| MOORE, REVA R | 2 | 52.8% | +50.0% |
| WEINER, ARIELLE E | 2 | 43.6% | +53.3% |
| JARRETT, SCOTT L | 1 | 52.0% | +47.3% |
| KANG, TIMOTHY J | 1 | 45.7% | +26.8% |
| GARG, YOGESH C | 1 | 61.7% | +33.4% |
| HEFLIN, BRIAN ADAMS | 1 | 39.5% | +32.4% |
| ROSEN, NICHOLAS D | 1 | 70.4% | +22.4% |
| WU, NICHOLAS S | 1 | 52.4% | +31.4% |
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 |
|---|---|---|---|
| 18113868 | DYNAMIC REPLENISHMENT OF ITEMS STAGED TO A RAPID FULFILLMENT AREA IN ASSOCIATION WITH AN ONLINE CONCIERGE SYSTEM | MUTSCHLER, JOSEPH M | 52d overdue |
| 18079317 | SELECTING PICKERS FOR SERVICE REQUESTS BASED ON OUTPUT OF COMPUTER MODEL TRAINED TO PREDICT ACCEPTANCES | LUDWIG, PETER L | 38d overdue |
| 18141397 | DETERMINING LIMITS FOR ATTRIBUTES OF AN ORDER FOR FULFILLMENT BY A PICKER USING A MACHINE-LEARNING MODEL | MOORE, REVA R | 30d overdue |
| 18140210 | Feature Recommendations for Machine Learning Models Using Trained Feature Prediction Model | WU, NICHOLAS S | 25d overdue |
| 18213764 | SUGGESTING FULFILLMENT SOURCES FOR A USER AT A NEW LOCATION BASED ON USER'S HISTORICAL ACTIVITY | KANG, TIMOTHY J | 9d overdue |
| 17478411 | RANKING SUGGESTIONS FOR COMPLETING A SEARCH QUERY BASED ON LIKELIHOOD OF A USER INCLUDING ITEMS CORRESPONDING TO THE SUGGESTIONS IN AN ORDER | WEINER, ARIELLE E | 4d overdue |
| 18129464 | PREDICTIVE PICKING OF ITEMS FOR PREPOPULATING A SHOPPING CART FOR A SHOPPER | WEINER, ARIELLE E | 15d |
| 18326900 | Predicting Replacement Items using a Machine-Learning Replacement Model | GARG, YOGESH C | 16d |
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 8 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18141397 | DETERMINING LIMITS FOR ATTRIBUTES OF AN ORDER FOR FULFILLMENT BY A PICKER USING A MACHINE-LEARNING MODEL | MOORE, REVA R | 30d overdue |
| 18140210 | Feature Recommendations for Machine Learning Models Using Trained Feature Prediction Model | WU, NICHOLAS S | 25d overdue |
| 18213764 | SUGGESTING FULFILLMENT SOURCES FOR A USER AT A NEW LOCATION BASED ON USER'S HISTORICAL ACTIVITY | KANG, TIMOTHY J | 9d overdue |
| 17478411 | RANKING SUGGESTIONS FOR COMPLETING A SEARCH QUERY BASED ON LIKELIHOOD OF A USER INCLUDING ITEMS CORRESPONDING TO THE SUGGESTIONS IN AN ORDER | WEINER, ARIELLE E | 4d overdue |
| 18129464 | PREDICTIVE PICKING OF ITEMS FOR PREPOPULATING A SHOPPING CART FOR A SHOPPER | WEINER, ARIELLE E | 15d |
| 18326900 | Predicting Replacement Items using a Machine-Learning Replacement Model | GARG, YOGESH C | 16d |
| 18214316 | TRAINED MODELS FOR PREDICTING TIMES FOR COMPLETION OF TASKS FOR AN ORDER PLACED WITH AN ONLINE SYSTEM AND DETERMINING REMEDIAL ACTIONS | JARRETT, SCOTT L | 29d |
| 18214150 | MACHINE-LEARNED MODEL FOR PERSONALIZING SERVICE OPTIONS IN AN ONLINE CONCIERGE SYSTEM USING LOCATION FEATURES | FRUNZI, VICTORIA E. | 61d |
| Art Unit | Apps |
|---|---|
| 3689 | 6 |
| 3627 | 6 |
| 3624 | 3 |
| 3621 | 2 |
| 3688 | 2 |
| 3625 | 1 |
| 3628 | 1 |
| 2148 | 1 |
| 3600 | 1 |
| 3692 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18214150 | MACHINE-LEARNED MODEL FOR PERSONALIZING SERVICE OPTIONS IN AN ONLINE CONCIERGE SYSTEM USING LOCATION FEATURES | FRUNZI, VICTORIA E. | 3689 | §101 | Non-Final OA | 61d | Pending | Jun 26, 2023 |
| 18214316 | TRAINED MODELS FOR PREDICTING TIMES FOR COMPLETION OF TASKS FOR AN ORDER PLACED WITH AN ONLINE SYSTEM AND DETERMINING REMEDIAL ACTIONS | JARRETT, SCOTT L | 3625 | §101 | Non-Final OA | 29d | Pending | Jun 26, 2023 |
| 18213764 | SUGGESTING FULFILLMENT SOURCES FOR A USER AT A NEW LOCATION BASED ON USER'S HISTORICAL ACTIVITY | KANG, TIMOTHY J | 3689 | §101 | Non-Final OA | 9d overdue | Pending | Jun 23, 2023 |
| 18213761 | OFFLINE SIMULATION TO TEST AN EFFECT OF A CONFIGURABLE PARAMETER USED BY A CONTENT DELIVERY SYSTEM | BAGGOT, BREFFNI | 3621 | §101 | Non-Final OA | — | Pending | Jun 23, 2023 |
| 18326900 | Predicting Replacement Items using a Machine-Learning Replacement Model | GARG, YOGESH C | 3688 | §101§102 | Final Rejection | 16d | Pending | May 31, 2023 |
| 18203578 | ESTIMATED TIME OF ARRIVAL DETERMINATIONS IN AN ONLINE CONCIERGE SYSTEM | HEFLIN, BRIAN ADAMS | 3628 | §101 | Non-Final OA | — | Pending | May 30, 2023 |
| 18199938 | User Interface for Obtaining Picker Intent Signals for Training Machine Learning Models | ROSEN, NICHOLAS D | 3689 | §101 | Non-Final OA | — | Pending | May 20, 2023 |
| 18141397 | DETERMINING LIMITS FOR ATTRIBUTES OF AN ORDER FOR FULFILLMENT BY A PICKER USING A MACHINE-LEARNING MODEL | MOORE, REVA R | 3627 | §101 | Non-Final OA | 30d overdue | Pending | Apr 29, 2023 |
| 18141394 | WAREHOUSE ITEM ASSORTMENT COMPARISON AND DISPLAY CUSTOMIZATION | MOORE, REVA R | 3627 | §101§103 | Non-Final OA | — | Pending | Apr 29, 2023 |
| 18140210 | Feature Recommendations for Machine Learning Models Using Trained Feature Prediction Model | WU, NICHOLAS S | 2148 | §101§103§112 | Final Rejection | 25d overdue | Pending | Apr 27, 2023 |
| 18129447 | AUTOMATIC KEYWORD GROUPING FOR CAMPAIGN BID CUSTOMIZATION | ASHRAF, WASEEM | 3600 | §101 | Non-Final OA | — | Pending | Mar 31, 2023 |
| 18129464 | PREDICTIVE PICKING OF ITEMS FOR PREPOPULATING A SHOPPING CART FOR A SHOPPER | WEINER, ARIELLE E | 3689 | §101 | Final Rejection | 15d | Pending | Mar 31, 2023 |
| 18113868 | DYNAMIC REPLENISHMENT OF ITEMS STAGED TO A RAPID FULFILLMENT AREA IN ASSOCIATION WITH AN ONLINE CONCIERGE SYSTEM | MUTSCHLER, JOSEPH M | 3627 | §101 | Final Rejection | 52d overdue | Pending | Feb 24, 2023 |
| 18172956 | VERIFYING ITEMS IN A SHOPPING CART BASED ON WEIGHTS MEASURED FOR THE ITEMS | CHISM, STEVEN R | 3692 | §103 | Non-Final OA | 18d overdue | Pending | Feb 22, 2023 |
| 18084938 | OFFLINE SIMULATION OF MULTIPLE EXPERIMENTS WITH VARIANT ADJUSTMENTS | BAGGOT, BREFFNI | 3621 | §101 | Non-Final OA | — | Pending | Dec 20, 2022 |
| 18079317 | SELECTING PICKERS FOR SERVICE REQUESTS BASED ON OUTPUT OF COMPUTER MODEL TRAINED TO PREDICT ACCEPTANCES | LUDWIG, PETER L | 3627 | §101§103 | Final Rejection | 38d overdue | Pending | Dec 12, 2022 |
| 17982941 | ASSIGNING TEST PERIODS OF GEOGRAPHIC REGIONS TO TREATMENT OR CONTROL GROUPS FOR A/B TESTING | EL-BATHY, MOHAMED N | 3624 | §101 | Final Rejection | — | Pending | Nov 08, 2022 |
| 17977759 | GENERATING A SCHEDULE FOR A PICKER OF AN ONLINE CONCIERGE SYSTEM BASED ON AN EARNINGS GOAL AND AVAILABILITY INFORMATION | GAVIN, KRISTIN ELIZABETH | 3624 | §101 | Final Rejection | — | Pending | Oct 31, 2022 |
| 17935916 | ITEM ATTRIBUTE DETERMINATION USING A CO-ENGAGEMENT GRAPH | BYRD, UCHE SOWANDE | 3624 | — | Non-Final OA | — | Pending | Sep 27, 2022 |
| 17900744 | ITEM AVAILABILITY MODEL PRODUCING ITEM VERIFICATION NOTIFICATIONS | FRUNZI, VICTORIA E. | 3689 | §101§102§103 | Final Rejection | — | Pending | Aug 31, 2022 |
| 17855793 | DETERMINING EFFICIENT ROUTES IN A COMPLEX SPACE USING HIERARCHICAL INFORMATION AND SPARSE DATA | WERONSKI, MATTHEW S | 3627 | §103 | Non-Final OA | — | Pending | Jul 01, 2022 |
| 17846887 | MACHINE LEARNED MODEL FOR MANAGING FOUNDATIONAL ITEMS IN CONCIERGE SYSTEM | BARGEON, BRITTANY E | 3688 | §101 | Final Rejection | — | Pending | Jun 22, 2022 |
| 17524491 | DIRECTLY IDENTIFYING ITEMS FROM AN ITEM CATALOG SATISFYING A RECEIVED QUERY USING A MODEL DETERMINING MEASURES OF SIMILARITY BETWEEN ITEMS IN THE ITEM CATALOG AND THE QUERY | GOYEA, OLUSEGUN | 3627 | §101 | Final Rejection | — | Pending | Nov 11, 2021 |
| 17478411 | RANKING SUGGESTIONS FOR COMPLETING A SEARCH QUERY BASED ON LIKELIHOOD OF A USER INCLUDING ITEMS CORRESPONDING TO THE SUGGESTIONS IN AN ORDER | WEINER, ARIELLE E | 3689 | §101 | Non-Final OA | 4d overdue | Pending | Sep 17, 2021 |
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