Detailed information about the 100 most recent patent applications.
| Application Number | Title | Filing Date | Disposal Date | Disposition | Time (months) | Office Actions | Restrictions | Interview | Appeal |
|---|---|---|---|---|---|---|---|---|---|
| 17139958 | SYSTEM AND METHODS FOR HETEROGENEOUS CONFIGURATION OPTIMIZATION FOR DISTRIBUTED SERVERS IN THE CLOUD | December 2020 | August 2024 | Allow | 44 | 2 | 0 | No | No |
| 17129406 | METHOD FOR DETERMINING CONTAINER TO BE MIGRATED AND NON-TRANSITORY COMPUTER-READABLE MEDIUM | December 2020 | April 2024 | Allow | 40 | 2 | 0 | Yes | No |
| 17127747 | REDUCING THE STARTUP LATENCY OF FUNCTIONS IN A FAAS INFRASTRUCTURE | December 2020 | February 2024 | Allow | 38 | 1 | 0 | No | No |
| 17124046 | AUTOMATIC SELF-ADJUSTING SOFTWARE IMAGE RECOMMENDATION | December 2020 | January 2024 | Allow | 37 | 1 | 0 | Yes | No |
| 17118281 | NETWORK PERFORMANCE DRIVEN COMPUTE WORKLOAD PLACEMENT | December 2020 | May 2024 | Allow | 41 | 2 | 0 | Yes | No |
| 17115090 | CONTAINERIZED COMPUTING ENVIRONMENTS | December 2020 | January 2024 | Allow | 37 | 1 | 0 | No | No |
| 17111502 | ACTIVATION POLICIES FOR WORKFLOWS | December 2020 | January 2024 | Allow | 37 | 1 | 0 | Yes | No |
| 17109509 | VERIFYING SOFTWARE MALFUNCTION SOURCES AMONG DISPARATE CODE SOURCES | December 2020 | September 2021 | Allow | 9 | 2 | 0 | Yes | No |
| 17106469 | DATA PROCESSING AND SCANNING SYSTEMS FOR ASSESSING VENDOR RISK | November 2020 | February 2021 | Allow | 3 | 1 | 0 | No | No |
| 16949897 | DYNAMICALLY CONFIGURING A PROCESS BASED ON ENVIRONMENTAL CHARACTERISTICS MONITORED BY A MOBILE DEVICE | November 2020 | September 2023 | Allow | 34 | 2 | 0 | Yes | No |
| 16953202 | METHOD AND APPARATUS FOR SCALING A CUSTOM RESOURCE WITH CUSTOM METRICS IN A CONTAINERIZED APPLICATION HANDLING SYSTEM | November 2020 | October 2023 | Allow | 35 | 3 | 0 | Yes | No |
| 16951697 | AUTOMATED ROLLBACK | November 2020 | August 2023 | Allow | 32 | 2 | 0 | Yes | No |
| 17095307 | Optimizing Hybrid Cloud Usage | November 2020 | September 2024 | Abandon | 46 | 4 | 0 | Yes | No |
| 17081529 | GOAL-DIRECTED SOFTWARE-DEFINED NUMA WORKING SET MANAGEMENT | October 2020 | February 2024 | Allow | 40 | 1 | 1 | Yes | No |
| 17077352 | COMPUTE RESOURCES MANAGEMENT VIA VIRTUAL SERVICE CONTEXTS (VSC) IN COMPUTE CLUSTERS | October 2020 | November 2023 | Allow | 36 | 1 | 0 | Yes | No |
| 17072115 | DISTRIBUTED NETWORK PLUGIN AGENTS FOR CONTAINER NETWORKING | October 2020 | July 2023 | Allow | 33 | 1 | 0 | No | No |
| 17070042 | CONSTRUCTING SOFTWARE DELTA UPDATES FOR CONTROLLER SOFTWARE AND ABNORMALITY DETECTION BASED ON TOOLCHAIN | October 2020 | January 2021 | Allow | 3 | 1 | 0 | Yes | No |
| 17028637 | ENHANCED ATTACHABLE WRITABLE VOLUMES IN VDI BASED ON DATA REQUIREMENTS | September 2020 | October 2023 | Allow | 37 | 2 | 0 | No | No |
| 16977892 | VM PERFORMANCE GUARANTEEING SYSTEM AND VM PERFORMANCE GUARANTEEING METHOD | September 2020 | October 2023 | Allow | 37 | 1 | 0 | Yes | No |
| 17007249 | MANAGEMENT INSTRUMENTATION AND DISCOVERY (MID) SERVER SUPPORT FOR EXECUTING AUTOMATED FLOWS WITHIN A CLOUD BASED SYSTEM | August 2020 | March 2023 | Allow | 31 | 2 | 0 | Yes | No |
| 17002233 | MEMORY COPY DURING VIRTUAL MACHINE MIGRATION IN A VIRTUALIZED COMPUTING SYSTEM | August 2020 | January 2024 | Allow | 41 | 3 | 0 | Yes | No |
| 16994085 | Clustering Processes Using Traffic Data | August 2020 | January 2023 | Allow | 29 | 1 | 0 | No | No |
| 16984422 | SYSTEMS AND METHODS FOR COMPUTING A SUCCESS PROBABILITY OF A SESSION LAUNCH USING STOCHASTIC AUTOMATA | August 2020 | May 2023 | Allow | 33 | 1 | 0 | Yes | No |
| 16944003 | USER PROFILE MANAGEMENT FOR NON-DOMAIN JOINED INSTANCE VIRTUAL MACHINES | July 2020 | November 2023 | Allow | 40 | 3 | 0 | Yes | No |
| 16940780 | Method for Accessing Remote Acceleration Device by Virtual Machine, and System | July 2020 | July 2023 | Abandon | 36 | 2 | 0 | No | No |
| 16939385 | VIRTUAL MACHINE MANAGEMENT METHOD USING VIRTUAL MACHINE DEPLOYMENT SIMULATION | July 2020 | December 2022 | Allow | 28 | 1 | 0 | No | No |
| 16938944 | INFERENCE ENGINE FOR CONFIGURATION PARAMETERS IN A NETWORK FUNCTIONS VIRTUALIZATION ORCHESTRATOR | July 2020 | April 2023 | Allow | 33 | 1 | 0 | Yes | No |
| 16928835 | DYNAMICALLY MOVING VIRTUAL MACHINE (VM) DATA BASED UPON CONTEXT | July 2020 | January 2023 | Allow | 30 | 1 | 0 | Yes | No |
| 16916051 | SYSTEMS, METHODS, AND MEDIA FOR TRUSTED HYPERVISORS | June 2020 | July 2024 | Allow | 49 | 5 | 0 | No | No |
| 16911144 | RIGHTSIZING VIRTUAL MACHINE DEPLOYMENTS IN A CLOUD COMPUTING ENVIRONMENT | June 2020 | February 2024 | Allow | 44 | 3 | 2 | Yes | No |
| 16909740 | SYSTEMS AND METHODS TO DECREASE THE SIZE OF A COMPOUND VIRTUAL APPLIANCE FILE | June 2020 | May 2022 | Allow | 23 | 0 | 0 | No | No |
| 16895877 | PEER-TO-PEER DATA COMMUNICATION BETWEEN DIFFERENT APPLICATIONS | June 2020 | February 2021 | Allow | 8 | 1 | 0 | No | No |
| 16871387 | USER INTERFACE COMMON COMPONENTS AND SCALABLE INTEGRABLE REUSABLE ISOLATED USER INTERFACE | May 2020 | January 2021 | Allow | 9 | 1 | 0 | Yes | No |
| 16869195 | ALLOCATING RESOURCES FOR A MACHINE LEARNING MODEL | May 2020 | September 2021 | Allow | 17 | 3 | 0 | Yes | No |
| 16828732 | VERIFYING SOFTWARE MALFUNCTION SOURCES AMONG DISPARATE CODE SOURCES | March 2020 | September 2020 | Allow | 6 | 1 | 0 | Yes | No |
| 16827376 | ALLOCATING RESOURCES FOR A MACHINE LEARNING MODEL | March 2020 | June 2021 | Allow | 14 | 2 | 0 | No | No |
| 16803558 | METHOD OF SELECTING A MACHINE LEARNING MODEL FOR PERFORMANCE PREDICTION BASED ON VERSIONING INFORMATION | February 2020 | July 2022 | Allow | 28 | 1 | 0 | Yes | No |
| 16800914 | COLLECTING CAPACITY DATA OF VIRTUAL MACHINES BY LEVERAGING AGENT DATA | February 2020 | January 2023 | Allow | 34 | 1 | 0 | Yes | No |
| 16786656 | ENABLING CONDITIONAL COMPUTING RESOURCE TERMINATIONS BASED ON FORECASTED CAPACITY AVAILABILITY | February 2020 | January 2023 | Allow | 35 | 1 | 0 | Yes | No |
| 16781992 | INTEGRATING MULTIPLE DISTRIBUTED DATA PROCESSING SERVERS WITH DIFFERENT DATA PARTITIONING AND ROUTING MECHANISMS, RESOURCE SHARING POLICIES AND LIFECYCLES INTO A SINGLE PROCESS | February 2020 | December 2020 | Allow | 10 | 1 | 0 | No | No |
| 16773004 | NON-VOLATILE MEMORY (NVM) BASED METHOD FOR PERFORMANCE ACCELERATION OF CONTAINERS | January 2020 | May 2022 | Allow | 28 | 1 | 0 | No | No |
| 16739870 | JOB SCHEDULING BASED ON JOB EXECUTION HISTORY | January 2020 | July 2022 | Allow | 30 | 5 | 0 | Yes | No |
| 16710261 | IMPROVED VIRTUAL MACHINE DEPLOYMENT METHOD AND OPERATION AND MMAINTENANCE MANEGEMENT VIRTUAL MACHINE | December 2019 | September 2022 | Allow | 33 | 1 | 0 | No | No |
| 16699943 | EXECUTING ALGORITHMS IN PARALLEL | December 2019 | December 2022 | Allow | 37 | 3 | 0 | No | No |
| 16699823 | TIME FRAME BOUNDED EXECUTION OF COMPUTATIONAL ALGORITHMS | December 2019 | November 2020 | Allow | 11 | 1 | 0 | Yes | No |
| 16698431 | Automated Management of Machine Images | November 2019 | July 2023 | Allow | 43 | 3 | 0 | Yes | No |
| 16692621 | MEASURING THE VULNERABILITY OF AI MODULES TO SPOOFING ATTEMPTS | November 2019 | August 2022 | Allow | 33 | 1 | 0 | No | No |
| 16683843 | COOPERATIVE SCHEDULING METHOD AND SYSTEM FOR COMPUTING RESOURCE AND NETWORK RESOURCE OF CONTAINER CLOUD PLATFORM | November 2019 | April 2021 | Allow | 17 | 1 | 0 | No | No |
| 16682877 | VIRTUAL MACHINE MIGRATION DETECTION BY A HOSTED OPERATING SYSTEM | November 2019 | August 2022 | Allow | 33 | 1 | 0 | Yes | No |
| 16682571 | CONSTRUCTING SOFTWARE DELTA UPDATES FOR CONTROLLER SOFTWARE AND ABNORMALITY DETECTION BASED ON TOOLCHAIN | November 2019 | July 2020 | Allow | 8 | 1 | 0 | Yes | No |
| 16678888 | EDGE SERVER CPU WITH DYNAMIC DETERMINISTIC SCALING | November 2019 | December 2022 | Allow | 38 | 2 | 0 | No | No |
| 16662893 | SOFTWARE CONTAINER REPLICATION USING GEOGRAPHIC LOCATION AFFINITY IN A DISTRIBUTED COMPUTING ENVIRONMENT | October 2019 | June 2022 | Allow | 32 | 1 | 0 | Yes | No |
| 16660341 | SECURITY RISK LOAD BALANCING SYSTEMS AND METHODS | October 2019 | June 2022 | Allow | 31 | 1 | 0 | No | No |
| 16601483 | VIRTUALIZED BACKGROUND ACTIVATIONS | October 2019 | June 2023 | Allow | 44 | 3 | 0 | Yes | No |
| 16595669 | MACHINE LEARNING-BASED POWER CAPPING AND VIRTUAL MACHINE PLACEMENT IN CLOUD PLATFORMS | October 2019 | September 2021 | Allow | 24 | 0 | 0 | No | No |
| 16585173 | SYSTEM AND METHODS FOR PROVISIONING DIFFERENT VERSIONS OF A VIRTUAL APPLICATION | September 2019 | May 2021 | Allow | 20 | 0 | 0 | Yes | No |
| 16585507 | METHOD TO ENABLE THE PREVENTION OF CACHE THRASHING ON MEMORY MANAGEMENT UNIT (MMU)-LESS HYPERVISOR SYSTEMS | September 2019 | September 2021 | Allow | 24 | 0 | 0 | No | No |
| 16498607 | METHOD OF CONTROLLING VIRTUAL NETWORK FUNCTION, VIRTUAL NETWORK FUNCTION MANAGEMENT APPARATUS AND VIRTUAL NETWORK PROVIDING SYSTEM | September 2019 | August 2023 | Abandon | 46 | 4 | 0 | Yes | No |
| 16498043 | CONTROL APPARATUS, CONTROL SYSTEM, CONTROL METHOD, AND PROGRAM | September 2019 | December 2021 | Abandon | 26 | 1 | 0 | No | No |
| 16579497 | FULLY DYNAMIC VIRTUAL PROXIES FOR DATA PROTECTION | September 2019 | May 2022 | Allow | 32 | 2 | 0 | No | No |
| 16577053 | MODULAR PROCESS CONTROL SYSTEM | September 2019 | December 2022 | Allow | 39 | 3 | 1 | Yes | No |
| 16577771 | TIMED MULTI-THREAD ACCESS FOR HIGH-THROUGHPUT SLOW-RESPONSE SYSTEMS | September 2019 | January 2022 | Allow | 28 | 1 | 0 | Yes | No |
| 16578199 | ALLOCATING CLOUD RESOURCES IN ACCORDANCE WITH PREDICTED DEPLOYMENT GROWTH | September 2019 | December 2022 | Allow | 39 | 3 | 0 | Yes | No |
| 16576983 | RESOURCE MANAGEMENT FOR SOFTWARE CONTAINERS USING CONTAINER PROFILES | September 2019 | March 2022 | Allow | 29 | 2 | 0 | Yes | No |
| 16494932 | METHODS AND APPARATUSES FOR MULTI-TIERED VIRTUALIZED NETWORK FUNCTION SCALING | September 2019 | March 2022 | Abandon | 30 | 2 | 0 | No | No |
| 16570824 | EDGE COMPUTING SYSTEM | September 2019 | August 2021 | Allow | 23 | 0 | 1 | No | No |
| 16563983 | APPLICATION DEMAND-BASED MIGRATION OF VIRTUAL MACHINES IN LOGICAL CLUSTERS | September 2019 | March 2022 | Allow | 30 | 2 | 0 | Yes | No |
| 16491222 | VIRTUAL NETWORK SYSTEM, VIM, VIRTUAL NETWORK CONTROL METHOD AND RECORDING MEDIUM | September 2019 | April 2021 | Allow | 19 | 0 | 0 | No | No |
| 16556521 | ADAPTIVE WORLD SWITCHING | August 2019 | September 2021 | Allow | 25 | 1 | 0 | No | No |
| 16557392 | DATA PROCESSING AND SCANNING SYSTEMS FOR ASSESSING VENDOR RISK | August 2019 | July 2020 | Allow | 11 | 2 | 0 | Yes | No |
| 16557620 | SYSTEM AND METHOD OF MANAGING A HARDWARE SWITCH AND A HYPERVISOR AS ONE LOGICAL ENTITY | August 2019 | December 2021 | Abandon | 27 | 1 | 0 | No | No |
| 16554476 | TASK BASED SERVICE MANAGEMENT PLATFORM | August 2019 | April 2021 | Allow | 19 | 0 | 0 | No | No |
| 16553215 | Dynamic Resource Optimization | August 2019 | July 2021 | Allow | 23 | 1 | 1 | Yes | No |
| 16553976 | PROCESSING APPARATUS, PROCESSING METHOD, AND COMPUTER PROGRAM PRODUCT FOR CONTROLLING TIMING OF DATA ACCESSING TO A MEMORY | August 2019 | April 2023 | Allow | 43 | 5 | 0 | Yes | No |
| 16488864 | COMMUNICATION PROCESSING DEVICE, INFORMATION PROCESSING DEVICE, AND COMMUNICATION PROCESSING DEVICE CONTROL METHOD | August 2019 | February 2022 | Allow | 29 | 1 | 0 | No | No |
| 16550327 | MEMORY-AWARE PLACEMENT FOR VIRTUAL GPU ENABLED SYSTEMS | August 2019 | November 2021 | Allow | 27 | 1 | 0 | No | No |
| 16545083 | COMMUNICATION METHOD FOR VIRTUAL MACHINES, ELECTRONIC DEVICE, AND NON-TRANSITORY COMPUTER READABLE STORAGE MEDIUM | August 2019 | August 2021 | Allow | 24 | 2 | 0 | Yes | No |
| 16541808 | VIRTUAL MACHINE DEPLOYMENT | August 2019 | December 2021 | Allow | 28 | 2 | 0 | Yes | No |
| 16537508 | VIRTUAL MACHINE MOBILITY FOR VIRTUAL MACHINES USING REMOTE DIRECT MEMORY ACCESS CONNECTIONS | August 2019 | September 2021 | Allow | 25 | 2 | 0 | Yes | No |
| 16532084 | EXCHANGING RUNTIME STATE INFORMATION BETWEEN DATACENTERS USING A CONTROLLER BRIDGE | August 2019 | September 2021 | Allow | 25 | 1 | 0 | Yes | No |
| 16532098 | EXCHANGING RUNTIME STATE INFORMATION BETWEEN DATACENTERS WITH A GATEWAY USING A CONTROLLER BRIDGE | August 2019 | December 2022 | Allow | 40 | 3 | 0 | Yes | No |
| 16527225 | SYSTEM AND METHOD FOR VALIDATING VIRTUAL STORAGE APPLIANCE DEPLOYMENT | July 2019 | December 2021 | Allow | 28 | 2 | 0 | Yes | No |
| 16528491 | DEPLOYING MICROSERVICES INTO VIRTUALIZED COMPUTING SYSTEMS | July 2019 | July 2021 | Allow | 24 | 1 | 0 | Yes | No |
| 16523819 | GUEST-DRIVEN VIRTUAL MACHINE SNAPSHOTS | July 2019 | June 2022 | Allow | 34 | 3 | 0 | Yes | No |
| 16523796 | USER DEVICE COMPLIANCE-PROFILE-BASED ACCESS TO VIRTUAL SESSIONS AND SELECT VIRTUAL SESSION CAPABILITIES | July 2019 | July 2021 | Allow | 23 | 1 | 0 | No | No |
| 16520939 | TAG ASSISTED CLOUD RESOURCE IDENTIFICATION FOR ONBOARDING AND APPLICATION BLUEPRINT CONSTRUCTION | July 2019 | October 2021 | Allow | 27 | 3 | 0 | Yes | No |
| 16520080 | AVOIDING POWER-ON FAILURES IN VIRTUALIZED GPUS | July 2019 | February 2021 | Allow | 19 | 0 | 0 | No | No |
| 16517426 | HYPERVISOR ASSISTED APPLICATION VIRTUALIZATION | July 2019 | January 2022 | Allow | 30 | 1 | 0 | Yes | No |
| 16511872 | QUALITY OF SERVICE SCHEDULING WITH WORKLOAD PROFILES | July 2019 | March 2021 | Allow | 20 | 1 | 0 | No | No |
| 16506952 | MANAGEMENT OF DEPENDENCIES BETWEEN CLUSTERS IN A COMPUTING ENVIRONMENT | July 2019 | February 2022 | Allow | 32 | 2 | 0 | No | No |
| 16505579 | PER REQUEST COMPUTER SYSTEM INSTANCES | July 2019 | March 2021 | Allow | 20 | 1 | 0 | Yes | No |
| 16503404 | SYSTEMS AND METHODS FOR REPURPOSING VIRTUAL MACHINES | July 2019 | November 2020 | Allow | 17 | 1 | 0 | No | No |
| 16502953 | CONSTRUCTING SOFTWARE DELTA UPDATES FOR CONTROLLER SOFTWARE AND ABNORMALITY DETECTION BASED ON TOOLCHAIN | July 2019 | October 2019 | Allow | 3 | 1 | 0 | No | No |
| 16459347 | Security Module With Multiple Independent Physical and Virtual Lanes | July 2019 | March 2022 | Allow | 33 | 2 | 0 | No | No |
| 16449949 | GENERATING NARRATIVES FOR OPTIMIZED COMPUTE PLATFORMS | June 2019 | June 2021 | Allow | 23 | 2 | 1 | Yes | No |
| 16472180 | DYNAMIC MANAGEMENT OF MONITORING TASKS IN A CLOUD ENVIRONMENT | June 2019 | June 2021 | Allow | 24 | 2 | 0 | Yes | No |
| 16468312 | ADAPTIVE COMPUTING RESOURCE ALLOCATION APPROACH FOR VIRTUAL NETWORK FUNCTIONS | June 2019 | August 2021 | Allow | 27 | 1 | 0 | No | No |
| 16435699 | USER INTERFACE COMMON COMPONENTS AND SCALABLE INTEGRABLE REUSABLE ISOLATED USER INTERFACE | June 2019 | January 2020 | Allow | 7 | 0 | 0 | Yes | No |
| 16435938 | APPARATUS AND METHOD TO PROVIDE HELP INFORMATION TO A USER IN A TIMELY MANNER | June 2019 | May 2021 | Allow | 24 | 1 | 0 | No | No |
| 16428833 | Connectivity Migration in a Virtual Execution System | May 2019 | April 2021 | Allow | 23 | 0 | 0 | Yes | No |
This analysis examines appeal outcomes and the strategic value of filing appeals for examiner DASCOMB, JACOB D.
With a 0.0% reversal rate, the PTAB affirms the examiner's rejections in the vast majority of cases. This reversal rate is in the bottom 25% across the USPTO, indicating that appeals face significant challenges here.
Filing a Notice of Appeal can sometimes lead to allowance even before the appeal is fully briefed or decided by the PTAB. This occurs when the examiner or their supervisor reconsiders the rejection during the mandatory appeal conference (MPEP § 1207.01) after the appeal is filed.
In this dataset, 50.0% of applications that filed an appeal were subsequently allowed. This appeal filing benefit rate is in the top 25% across the USPTO, indicating that filing appeals is particularly effective here. The act of filing often prompts favorable reconsideration during the mandatory appeal conference.
⚠ Appeals to PTAB face challenges. Ensure your case has strong merit before committing to full Board review.
✓ Filing a Notice of Appeal is strategically valuable. The act of filing often prompts favorable reconsideration during the mandatory appeal conference.
Examiner DASCOMB, JACOB D works in Art Unit 2199 and has examined 376 patent applications in our dataset. With an allowance rate of 89.1%, this examiner has an above-average tendency to allow applications. Applications typically reach final disposition in approximately 30 months.
Examiner DASCOMB, JACOB D's allowance rate of 89.1% places them in the 71% percentile among all USPTO examiners. This examiner has an above-average tendency to allow applications.
On average, applications examined by DASCOMB, JACOB D receive 2.19 office actions before reaching final disposition. This places the examiner in the 56% percentile for office actions issued. This examiner issues a slightly above-average number of office actions.
The median time to disposition (half-life) for applications examined by DASCOMB, JACOB D is 30 months. This places the examiner in the 59% percentile for prosecution speed. Prosecution timelines are slightly faster than average with this examiner.
Conducting an examiner interview provides a +21.7% benefit to allowance rate for applications examined by DASCOMB, JACOB D. This interview benefit is in the 65% percentile among all examiners. Recommendation: Interviews provide an above-average benefit with this examiner and are worth considering.
When applicants file an RCE with this examiner, 32.0% of applications are subsequently allowed. This success rate is in the 68% percentile among all examiners. Strategic Insight: RCEs show above-average effectiveness with this examiner. Consider whether your amendments or new arguments are strong enough to warrant an RCE versus filing a continuation.
This examiner enters after-final amendments leading to allowance in 23.8% of cases where such amendments are filed. This entry rate is in the 33% percentile among all examiners. Strategic Recommendation: This examiner shows below-average receptiveness to after-final amendments. You may need to file an RCE or appeal rather than relying on after-final amendment entry.
When applicants request a pre-appeal conference (PAC) with this examiner, 171.4% result in withdrawal of the rejection or reopening of prosecution. This success rate is in the 92% percentile among all examiners. Strategic Recommendation: Pre-appeal conferences are highly effective with this examiner compared to others. Before filing a full appeal brief, strongly consider requesting a PAC. The PAC provides an opportunity for the examiner and supervisory personnel to reconsider the rejection before the case proceeds to the PTAB.
This examiner withdraws rejections or reopens prosecution in 66.7% of appeals filed. This is in the 48% percentile among all examiners. Of these withdrawals, 50.0% occur early in the appeal process (after Notice of Appeal but before Appeal Brief). Strategic Insight: This examiner shows below-average willingness to reconsider rejections during appeals. Be prepared to fully prosecute appeals if filed.
When applicants file petitions regarding this examiner's actions, 30.0% are granted (fully or in part). This grant rate is in the 16% percentile among all examiners. Strategic Note: Petitions are rarely granted regarding this examiner's actions compared to other examiners. Ensure you have a strong procedural basis before filing a petition, as the Technology Center Director typically upholds this examiner's decisions.
Examiner's Amendments: This examiner makes examiner's amendments in 0.5% of allowed cases (in the 60% percentile). This examiner makes examiner's amendments more often than average to place applications in condition for allowance (MPEP § 1302.04).
Quayle Actions: This examiner issues Ex Parte Quayle actions in 0.0% of allowed cases (in the 16% percentile). This examiner rarely issues Quayle actions compared to other examiners. Allowances typically come directly without a separate action for formal matters.
Based on the statistical analysis of this examiner's prosecution patterns, here are tailored strategic recommendations:
Not Legal Advice: The information provided in this report is for informational purposes only and does not constitute legal advice. You should consult with a qualified patent attorney or agent for advice specific to your situation.
No Guarantees: We do not provide any guarantees as to the accuracy, completeness, or timeliness of the statistics presented above. Patent prosecution statistics are derived from publicly available USPTO data and are subject to data quality limitations, processing errors, and changes in USPTO practices over time.
Limitation of Liability: Under no circumstances will IronCrow AI be liable for any outcome, decision, or action resulting from your reliance on the statistics, analysis, or recommendations presented in this report. Past prosecution patterns do not guarantee future results.
Use at Your Own Risk: While we strive to provide accurate and useful prosecution statistics, you should independently verify any information that is material to your prosecution strategy and use your professional judgment in all patent prosecution matters.