Detailed information about the 100 most recent patent applications.
| Application Number | Title | Filing Date | Disposal Date | Disposition | Time (months) | Office Actions | Restrictions | Interview | Appeal |
|---|---|---|---|---|---|---|---|---|---|
| 19219859 | AI AGENT-DRIVEN INTERACTION MODEL FOR APPLICATIONS | May 2025 | September 2025 | Allow | 3 | 0 | 0 | Yes | No |
| 19206035 | METHODS, SYSTEMS, AND STORAGE MEDIA FOR COMPUTATION SCHEDULING BASED ON IIOT DATA CENTERS | May 2025 | August 2025 | Allow | 3 | 0 | 0 | No | No |
| 19179572 | SEQUENTIAL WORKFLOW ORCHESTRATION MODEL SYSTEM AND METHOD | April 2025 | October 2025 | Allow | 7 | 1 | 0 | No | No |
| 19068551 | METHOD OF HANDLING A FAILURE IN A TASK PIPELINE BETWEEN A SOURCE OF ALERTS AND A SECURITY INCIDENT & EVENT MANAGEMENT (SIEM) SYSTEM | March 2025 | May 2025 | Allow | 3 | 0 | 0 | Yes | No |
| 19064870 | SYSTEMS AND METHODS FOR GENERATING AND EXECUTING FUNCTION CALLS USING MACHINE LEARNING | February 2025 | January 2026 | Allow | 10 | 2 | 0 | Yes | No |
| 19029511 | AUTOMATED RIGHTSIZING OF CONTAINERIZED APPLICATION WITH OPTIMIZED HORIZONTAL SCALING | January 2025 | November 2025 | Allow | 10 | 1 | 0 | Yes | No |
| 18878029 | TASK SCHEDULING METHOD AND APPARATUS, ELECTRONIC DEVICE, AND STORAGE MEDIUM | December 2024 | March 2025 | Allow | 3 | 0 | 0 | Yes | No |
| 18983455 | RULES-BASED RESOURCE DISTRIBUTION | December 2024 | October 2025 | Allow | 10 | 2 | 0 | Yes | No |
| 18951880 | SECURITY INCIDENT & EVENT MANAGEMENT CASE CREATION SYSTEM AND METHOD | November 2024 | January 2025 | Allow | 2 | 0 | 0 | Yes | No |
| 18917643 | CONTEXT-AWARE APPLICATION PROVISIONING | October 2024 | July 2025 | Allow | 9 | 2 | 0 | Yes | No |
| 18901209 | METHOD FOR THE COMPUTER-AIDED EXECUTION OF A TECHNICAL PROCESS IN PROCESSING UNITS, COMPUTING ENVIRONMENT, AND STORAGE MEDIUM | September 2024 | June 2025 | Allow | 9 | 0 | 0 | Yes | No |
| 18900098 | BUILDING MANAGEMENT SYSTEMS WITH SUSTAINABILITY IMPROVEMENT ARCHITECTURES | September 2024 | July 2025 | Allow | 10 | 1 | 0 | Yes | No |
| 18844249 | Method, System, and Computer Program Product for Dynamic Data Allocation to Nodes in Distributed Systems | September 2024 | March 2025 | Allow | 6 | 0 | 0 | Yes | No |
| 18794248 | SECURITY INCIDENT & EVENT MANAGEMENT CASE CREATION SYSTEM AND METHOD | August 2024 | October 2024 | Allow | 3 | 0 | 0 | No | No |
| 18785954 | SYSTEMS AND METHODS TO FACILITATE ADAPTIVE RESOURCE CAPACITY PREDICTION AND CONTROL USING CLOUD INFRASTRUCTURES | July 2024 | December 2024 | Allow | 4 | 0 | 0 | Yes | No |
| 18745825 | OFFLOADING PACKET PROCESSING PROGRAMS FROM VIRTUAL MACHINES TO A HYPERVISOR AND EFFICIENTLY EXECUTING THE OFFLOADED PACKET PROCESSING PROGRAMS | June 2024 | March 2025 | Allow | 9 | 0 | 0 | Yes | No |
| 18736305 | Examining A Cloud-Based Storage System Using Codified States | June 2024 | January 2026 | Allow | 20 | 2 | 0 | Yes | No |
| 18736094 | AUTOMATED RIGHTSIZING OF CONTAINERIZED APPLICATION WITH OPTIMIZED HORIZONTAL SCALING | June 2024 | September 2025 | Abandon | 16 | 1 | 0 | No | No |
| 18732305 | DYNAMICALLY SELECTING ARTIFICIAL INTELLIGENCE MODELS AND HARDWARE ENVIRONMENTS TO EXECUTE TASKS | June 2024 | April 2025 | Allow | 10 | 2 | 0 | Yes | No |
| 18680247 | DIFFERENTIAL CONTROL OF AGGREGATED CRYPTOGRAPHIC HARDWARE ASSETS | May 2024 | March 2025 | Allow | 10 | 2 | 0 | Yes | No |
| 18653936 | MAGNIFYING RESOURCES FOR A LOCATION | May 2024 | July 2024 | Allow | 3 | 0 | 0 | Yes | No |
| 18639016 | METHOD, DEVICE, COMPUTER DEVICE AND STORAGE DEVICE FOR REQUEST PROCESSING | April 2024 | June 2024 | Allow | 2 | 0 | 0 | Yes | No |
| 18636927 | MANAGING A DIGITAL ASSISTANT WORKFLOW | April 2024 | February 2025 | Allow | 10 | 2 | 0 | No | No |
| 18635907 | SYSTEMS AND METHODS OF AUTO-SCALING A VIRTUAL DESKTOP ENVIRONMENT | April 2024 | November 2024 | Allow | 7 | 0 | 0 | Yes | No |
| 18622214 | NEURAL PROCESSING DEVICE, NEURAL PROCESSING SYSTEM AND METHOD FOR PROCESSING COMMAND BRANCH OF NEURAL PROCESSING DEVICE | March 2024 | August 2024 | Allow | 4 | 0 | 0 | Yes | No |
| 18434110 | System and Method for Queuing Work within a Virtualized Scheduler Based on In-Unit Accounting of In-Unit Entries | February 2024 | September 2024 | Allow | 7 | 0 | 0 | Yes | No |
| 18394232 | HYBRID VIRTUAL GPU CO-SCHEDULING | December 2023 | November 2025 | Abandon | 23 | 2 | 0 | No | No |
| 18499901 | CLUSTER NODE RECOMMENDATION SYSTEM | November 2023 | January 2024 | Allow | 3 | 0 | 0 | Yes | No |
| 18364182 | MEASUREMENT SEQUENCE DETERMINATION FOR QUANTUM COMPUTING DEVICE | August 2023 | April 2024 | Allow | 8 | 0 | 0 | Yes | No |
| 18361529 | SERVER-BASED WORKFLOW MANAGEMENT USING PRIORITIES | July 2023 | August 2024 | Allow | 12 | 3 | 0 | Yes | No |
| 18351388 | DYNAMIC TASK ALLOCATION AND DATASTORE SCALING | July 2023 | October 2024 | Allow | 15 | 3 | 0 | Yes | No |
| 18343196 | Distributed Quantum Computing System | June 2023 | February 2024 | Allow | 8 | 0 | 0 | Yes | No |
| 18341588 | Generic Concurrency Restriction | June 2023 | March 2024 | Allow | 9 | 0 | 0 | Yes | No |
| 18339735 | RESOURCE PRE-FETCH USING AGE THRESHOLD | June 2023 | February 2024 | Allow | 8 | 0 | 0 | Yes | No |
| 18337566 | High Availability Multi-Single-Tenant Services | June 2023 | June 2024 | Allow | 12 | 1 | 0 | Yes | No |
| 18295344 | System and Method for Managing a Hybrid Compute Environment | April 2023 | August 2024 | Abandon | 17 | 2 | 0 | No | No |
| 18185296 | ARBITRARY DESTINATION CALLBACK INVOCATION BETWEEN A TRUSTED EXECUTION ENVIRONMENT AND A VIRTUAL MACHINE | March 2023 | August 2025 | Allow | 29 | 0 | 0 | No | No |
| 18180497 | System and Method for Queuing Work within a Virtualized Scheduler Based on In-Unit Accounting of In-Unit Entries | March 2023 | November 2023 | Allow | 8 | 1 | 0 | Yes | No |
| 18162546 | Reducing Cluster Start Up Time | January 2023 | March 2025 | Allow | 25 | 3 | 0 | Yes | No |
| 18093824 | INTERNET OF THINGS SOLUTION DEPLOYMENT IN HYBRID ENVIRONMENT | January 2023 | November 2023 | Allow | 11 | 1 | 0 | No | No |
| 18091691 | Automated Job Flow Cancellation for Multiple Task Routine Instance Errors in Many Task Computing | December 2022 | June 2023 | Allow | 6 | 0 | 0 | Yes | No |
| 18091569 | Data Object Preparation for Execution of Multiple Task Routine Instances in Many Task Computing | December 2022 | April 2023 | Allow | 4 | 0 | 0 | Yes | No |
| 18091672 | Message Queue Protocol for Sequential Execution of Related Task Routines in Many Task Computing | December 2022 | May 2023 | Allow | 4 | 0 | 0 | Yes | No |
| 18066632 | COMPILER MANAGED TENSOR PARALLEL EXECUTION | December 2022 | June 2025 | Allow | 30 | 0 | 0 | Yes | No |
| 17993552 | SYSTEMS AND METHODS OF AUTO-SCALING A VIRTUAL DESKTOP ENVIRONMENT | November 2022 | September 2025 | Allow | 34 | 0 | 0 | Yes | No |
| 17993529 | SYSTEMS AND METHODS OF AUTO-SCALING A VIRTUAL DESKTOP ENVIRONMENT | November 2022 | October 2025 | Allow | 35 | 0 | 0 | Yes | No |
| 17992550 | Resource Tapping Method, Resource Tapping Apparatus and Electronic Device | November 2022 | September 2025 | Allow | 34 | 1 | 0 | No | No |
| 18056400 | SUSTAINABILITY-BASED COMPUTING RESOURCE ALLOCATION | November 2022 | May 2023 | Allow | 6 | 0 | 0 | Yes | No |
| 17988237 | AUTOMATED TASK MANAGEMENT IN ANALYTICS COMPUTING SYSTEMS | November 2022 | November 2025 | Allow | 36 | 1 | 0 | No | No |
| 18055598 | SEMICONDUCTOR DEVICE, CONTROL METHOD FOR THE SAME, AND PROGRAM | November 2022 | December 2025 | Allow | 37 | 1 | 0 | No | No |
| 17985120 | Deep Learning Scheduler Toolkit | November 2022 | June 2025 | Allow | 31 | 0 | 0 | Yes | No |
| 18045742 | MEASUREMENT SEQUENCE DETERMINATION FOR QUANTUM COMPUTING DEVICE | October 2022 | March 2023 | Allow | 5 | 0 | 0 | Yes | No |
| 17916616 | RESOURCE CAPACITY MANAGEMENT IN CLOUDS | October 2022 | December 2025 | Allow | 38 | 2 | 0 | No | No |
| 17902520 | SYSTEMS AND METHODS OF AUTO-SCALING A VIRTUAL DESKTOP ENVIRONMENT | September 2022 | April 2023 | Allow | 8 | 1 | 0 | Yes | No |
| 17887113 | SYSTEMS AND METHODS FOR REAL-TIME PROCESSING | August 2022 | March 2024 | Allow | 19 | 2 | 0 | Yes | Yes |
| 17792252 | FAAS DISTRIBUTED COMPUTING METHOD AND APPARATUS | July 2022 | June 2023 | Allow | 11 | 1 | 0 | Yes | No |
| 17791484 | PLUG-IN FOR ENHANCING RESOURCE ELASTIC SCALING OF DISTRIBUTED DATA FLOW AND METHOD FOR ENHANCING PLUG-IN FOR ENHANCING RESOURCE ELASTIC SCALING OF DISTRIBUTED DATA FLOW | July 2022 | August 2023 | Allow | 13 | 1 | 0 | Yes | No |
| 17856606 | LCS LIFE-CYCLE MANAGEMENT SYSTEM | July 2022 | November 2025 | Allow | 40 | 1 | 0 | Yes | No |
| 17810472 | Scaling A Cloud-Based Storage System In Response To A Change In Workload | July 2022 | November 2023 | Allow | 16 | 2 | 0 | Yes | No |
| 17853564 | DYNAMIC RESOURCE ALLOCATION BASED ON QUALITY-OF-SERVICE PREDICTION | June 2022 | November 2025 | Allow | 41 | 1 | 0 | No | No |
| 17809115 | Enabling Virtual Functions on Storage Media | June 2022 | February 2023 | Allow | 8 | 0 | 0 | Yes | No |
| 17848669 | INTELLIGENT RESOURCE EVALUATOR SYSTEM FOR ROBOTIC PROCESS AUTOMATIONS | June 2022 | December 2024 | Allow | 30 | 0 | 0 | Yes | No |
| 17663861 | Dynamic Allocation of Resources | May 2022 | June 2023 | Allow | 13 | 1 | 0 | Yes | No |
| 17777323 | DATA PREPROCESSING FOR A SUPERVISED MACHINE LEARNING PROCESS | May 2022 | November 2025 | Abandon | 42 | 1 | 0 | No | No |
| 17734122 | DEPLOYMENT AND ISOLATION OF PLUGINS IN A VIRTUALIZED COMPUTING ENVIRONMENT | May 2022 | October 2023 | Allow | 17 | 2 | 0 | Yes | No |
| 17733075 | COMPUTING RESOURCE PREDICTION FOR OPTIMIZING RESOURCE UTILIZATION AND COMPUTING WORKLOAD DENSITY | April 2022 | March 2026 | Allow | 46 | 2 | 0 | Yes | No |
| 17733196 | Automated Job Flow Generation to Provide Object Views in Container-Supported Many Task Computing | April 2022 | August 2022 | Allow | 3 | 0 | 0 | Yes | No |
| 17733090 | AUTOMATED VIRTUAL MACHINE RESOURCE MANAGEMENT IN CONTAINER-SUPPORTED MANY TASK COMPUTING | April 2022 | August 2022 | Allow | 3 | 0 | 0 | Yes | No |
| 17726053 | INTERRUPTION DETECTION DURING AUTOMATED WORKFLOW | April 2022 | January 2026 | Allow | 45 | 2 | 0 | Yes | No |
| 17725482 | DEVICE FOR MANAGING VIRTUALIZED RESOURCES | April 2022 | April 2025 | Abandon | 35 | 1 | 0 | No | No |
| 17659775 | MACHINE LEARNING MODEL LAYER | April 2022 | October 2025 | Allow | 42 | 1 | 0 | Yes | No |
| 17721611 | RESOURCE PRE-FETCH USING AGE THRESHOLD | April 2022 | February 2023 | Allow | 10 | 0 | 0 | Yes | No |
| 17718692 | SYSTEM AND METHOD FOR DYNAMIC TASK SCHEDULING | April 2022 | March 2026 | Allow | 47 | 2 | 0 | Yes | No |
| 17657524 | Counters For Ensuring Transactional Ordering in I/O Agent | March 2022 | January 2026 | Allow | 46 | 2 | 0 | Yes | No |
| 17709229 | METHOD AND SYSTEM FOR DYNAMICALLY AND RELIABLY SCALING DATA PROCESSING PIPELINES IN A COMPUTING ENVIRONMENT | March 2022 | November 2022 | Allow | 7 | 1 | 0 | No | No |
| 17707767 | ALGORITHMICALLY OPTIMIZED DETERMINATION OF RESOURCE ASSIGNMENTS IN MACHINE REQUEST ANALYSES | March 2022 | September 2024 | Allow | 30 | 0 | 0 | Yes | No |
| 17696311 | SYSTEMS AND METHODS OF AUTO-SCALING A VIRTUAL DESKTOP ENVIRONMENT | March 2022 | December 2023 | Allow | 21 | 1 | 0 | Yes | No |
| 17695446 | VIRTUAL MACHINE MIGRATION BASED ON POWER UTILIZATION | March 2022 | March 2025 | Allow | 36 | 0 | 0 | Yes | No |
| 17694026 | OPTIMIZING RAN COMPUTE RESOURCES IN A VERTICALLY SCALED VRAN DEPLOYMENT | March 2022 | July 2025 | Allow | 40 | 1 | 0 | Yes | No |
| 17653215 | SYSTEM AND METHOD FOR COMPARING BEHAVIOR OF SOFTWARE COMPONENTS | March 2022 | September 2024 | Allow | 30 | 0 | 0 | Yes | No |
| 17682783 | Federated Area Coherency Across Multiple Devices in Many-Task Computing | February 2022 | May 2022 | Allow | 3 | 0 | 0 | Yes | No |
| 17680058 | System and Method for Queuing Work within a Virtualized Scheduler Based on In-Unit Accounting of In-Unit Entries | February 2022 | January 2023 | Allow | 11 | 0 | 0 | Yes | No |
| 17678702 | MANAGEMENT AND UTILIZATION OF NETWORK INTERFACE CARD RESOURCES FOR WORKLOAD EXECUTION | February 2022 | April 2025 | Allow | 37 | 1 | 0 | Yes | No |
| 17586571 | EXECUTING A NEURAL NETWORK GRAPH USING A NON-HOMOGENOUS SET OF RECONFIGURABLE PROCESSORS | January 2022 | August 2023 | Allow | 19 | 0 | 0 | Yes | No |
| 17582925 | TRAINING A NEURAL NETWORK USING A NON-HOMOGENOUS SET OF RECONFIGURABLE PROCESSORS | January 2022 | September 2023 | Allow | 19 | 0 | 0 | Yes | No |
| 17576828 | MULTI-THREADED TRAFFIC SHAPER | January 2022 | September 2024 | Allow | 32 | 0 | 0 | Yes | No |
| 17569092 | METHOD AND SYSTEM FOR PERFORMING PREDICTIVE COMPOSITIONS FOR COMPOSED INFORMATION HANDLING SYSTEMS USING TELEMETRY DATA | January 2022 | December 2024 | Allow | 35 | 0 | 0 | Yes | No |
| 17568591 | ROBUST RESOURCE REMOVAL FOR VIRTUAL MACHINES | January 2022 | January 2026 | Allow | 48 | 3 | 0 | Yes | No |
| 17563697 | COORDINATED PERFORMANCE CONTROLLER FAILOVER IN MANY TASK COMPUTING | December 2021 | April 2022 | Allow | 3 | 0 | 0 | Yes | No |
| 17564093 | Controlling Remote Electronic Device with Wearable Electronic Device | December 2021 | June 2025 | Allow | 41 | 5 | 0 | Yes | No |
| 17563034 | METHOD OF PERFORMING SPLITTING IN NEURAL NETWORK MODEL BY MEANS OF MULTI-CORE PROCESSOR, AND RELATED PRODUCT | December 2021 | May 2025 | Abandon | 41 | 1 | 0 | No | No |
| 17559251 | Multi-Cycle Scheduler with Speculative Picking of Micro-Operations | December 2021 | September 2025 | Allow | 45 | 3 | 0 | Yes | No |
| 17558237 | IMPLICIT STATUS IN MANY TASK COMPUTING | December 2021 | March 2022 | Allow | 3 | 0 | 0 | Yes | No |
| 17618797 | SYSTEM, METHOD AND COMPUTER-ACCESSIBLE MEDIUM FOR A DOMAIN DECOMPOSITION AWARE PROCESSOR ASSIGNMENT IN MULTICORE PROCESSING SYSTEM(S) | December 2021 | June 2024 | Allow | 30 | 0 | 0 | Yes | No |
| 17618016 | COMPUTER SYSTEM AND PROGRAM EXECUTION METHOD | December 2021 | May 2024 | Allow | 29 | 0 | 0 | No | No |
| 17547505 | Generic Concurrency Restriction | December 2021 | March 2023 | Allow | 15 | 1 | 0 | Yes | No |
| 17548303 | TASK EXECUTION METHOD, APPARATUS, DEVICE AND SYSTEM, AND STORAGE MEDIUM | December 2021 | October 2022 | Allow | 10 | 0 | 0 | Yes | No |
| 17539108 | WORKSTATION UPTIME, MAINTENANCE, AND REBOOT SERVICE | November 2021 | October 2025 | Allow | 46 | 4 | 0 | No | Yes |
| 17534943 | Job Shop Scheduling Method with Buffer Constraints Based on Improved Genetic Algorithm | November 2021 | February 2022 | Allow | 2 | 0 | 0 | Yes | No |
| 17613203 | METHOD, APPARATUS AND SYSTEM FOR HIGH PERFORMANCE PERIPHERAL COMPONENT INTERCONNECT DEVICE RESOURCE SHARING IN CLOUD ENVIRONMENTS | November 2021 | September 2025 | Abandon | 46 | 2 | 0 | No | No |
This analysis examines appeal outcomes and the strategic value of filing appeals for examiner PATEL, HIREN P.
With a 22.2% reversal rate, the PTAB affirms the examiner's rejections in the vast majority of cases. This reversal rate is below the USPTO average, indicating that appeals face more challenges here than typical.
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, 38.5% of applications that filed an appeal were subsequently allowed. This appeal filing benefit rate is above the USPTO average, suggesting that filing an appeal can be an effective strategy for prompting reconsideration.
⚠ 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 PATEL, HIREN P works in Art Unit 2196 and has examined 491 patent applications in our dataset. With an allowance rate of 84.1%, this examiner has an above-average tendency to allow applications. Applications typically reach final disposition in approximately 31 months.
Examiner PATEL, HIREN P's allowance rate of 84.1% places them in the 59% percentile among all USPTO examiners. This examiner has an above-average tendency to allow applications.
On average, applications examined by PATEL, HIREN P receive 1.75 office actions before reaching final disposition. This places the examiner in the 38% percentile for office actions issued. This examiner issues fewer office actions than average, which may indicate efficient prosecution or a more lenient examination style.
The median time to disposition (half-life) for applications examined by PATEL, HIREN P is 31 months. This places the examiner in the 54% percentile for prosecution speed. Prosecution timelines are slightly faster than average with this examiner.
Conducting an examiner interview provides a +39.3% benefit to allowance rate for applications examined by PATEL, HIREN P. This interview benefit is in the 87% percentile among all examiners. Recommendation: Interviews are highly effective with this examiner and should be strongly considered as a prosecution strategy. Per MPEP § 713.10, interviews are available at any time before the Notice of Allowance is mailed or jurisdiction transfers to the PTAB.
When applicants file an RCE with this examiner, 27.9% of applications are subsequently allowed. This success rate is in the 50% percentile among all examiners. Strategic Insight: RCEs show below-average effectiveness with this examiner. Carefully evaluate whether an RCE or continuation is the better strategy.
This examiner enters after-final amendments leading to allowance in 11.8% of cases where such amendments are filed. This entry rate is in the 12% percentile among all examiners. Strategic Recommendation: This examiner rarely enters after-final amendments compared to other examiners. You should generally plan to file an RCE or appeal rather than relying on after-final amendment entry. Per MPEP § 714.12, primary examiners have discretion in entering after-final amendments, and this examiner exercises that discretion conservatively.
When applicants request a pre-appeal conference (PAC) with this examiner, 47.6% result in withdrawal of the rejection or reopening of prosecution. This success rate is in the 42% percentile among all examiners. Note: Pre-appeal conferences show below-average success with this examiner. Consider whether your arguments are strong enough to warrant a PAC request.
This examiner withdraws rejections or reopens prosecution in 64.0% of appeals filed. This is in the 44% percentile among all examiners. Of these withdrawals, 34.4% 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, 21.2% are granted (fully or in part). This grant rate is in the 11% 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 0.4% of allowed cases (in the 58% 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 15% 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.