Detailed information about the 100 most recent patent applications.
| Application Number | Title | Filing Date | Disposal Date | Disposition | Time (months) | Office Actions | Restrictions | Interview | Appeal |
|---|---|---|---|---|---|---|---|---|---|
| 17130968 | NATIVE-IMAGE IN-MEMORY CACHE FOR CONTAINERIZED AHEAD-OF-TIME APPLICATIONS | December 2020 | December 2023 | Allow | 35 | 1 | 0 | Yes | No |
| 17118501 | PROGRAM GENERATING DEVICE, PROGRAM GENERATING METHOD, AND INFORMATION STORAGE MEDIUM | December 2020 | January 2024 | Allow | 37 | 1 | 0 | Yes | No |
| 15733854 | SERVERLESS LIFECYCLE MANAGEMENT DISPATCHER | November 2020 | December 2023 | Abandon | 37 | 1 | 0 | No | No |
| 17102474 | VIRTUALIZED FABRIC NAME SERVER FOR STORAGE AREA NETWORK | November 2020 | May 2023 | Allow | 30 | 1 | 0 | Yes | No |
| 17101327 | PERSISTENT VOLUME PLUGIN FOR CONTAINERS | November 2020 | June 2023 | Allow | 31 | 1 | 0 | Yes | No |
| 16952375 | TECHNIQUES TO MANAGE VIRTUAL CLASSES FOR STATISTICAL TESTS | November 2020 | April 2021 | Allow | 5 | 1 | 0 | Yes | No |
| 16951616 | METHODS AND SYSTEMS FOR REPRESENTING PROCESSING RESOURCES | November 2020 | July 2023 | Allow | 32 | 2 | 0 | Yes | No |
| 17095119 | METHOD AND APPARATUS FOR TRUSTED DEVICES USING TRUST DOMAIN EXTENSIONS | November 2020 | June 2024 | Allow | 43 | 1 | 0 | No | No |
| 17094542 | EMULATION AUTOMATION AND MODEL CHECKING | November 2020 | October 2022 | Allow | 23 | 0 | 0 | No | No |
| 17081793 | DIRECT ACCESS STORAGE FOR PERSISTENT SERVICES IN A VIRTUALIZED COMPUTING SYSTEM | October 2020 | March 2023 | Allow | 29 | 2 | 0 | No | No |
| 17077962 | DEEP LEARNING AUTOTUNING TASK OPTIMIZATION | October 2020 | December 2023 | Allow | 38 | 1 | 0 | Yes | No |
| 17075256 | METHOD AND SYSTEM OF HOST RESOURCE UTILIZATION REDUCTION | October 2020 | May 2023 | Allow | 31 | 1 | 0 | No | No |
| 17072196 | SYSTEMS AND METHODS FOR DETECTING ERRORS OF ASYNCHRONOUSLY ENQUEUED REQUESTS | October 2020 | January 2021 | Allow | 3 | 0 | 0 | Yes | No |
| 17068949 | KUBERNETES RESOURCE POLICY ENFORCEMENT | October 2020 | October 2022 | Allow | 24 | 1 | 0 | No | No |
| 17066362 | Virtual Machine Scheduling Method and System | October 2020 | June 2023 | Allow | 33 | 1 | 0 | Yes | No |
| 17044284 | SCHEDULING OF A PLURALITY OF GRAPHIC PROCESSING UNITS | September 2020 | January 2024 | Allow | 39 | 1 | 0 | No | No |
| 17041723 | MANAGING QUALITY OF STORAGE SERVICE IN VIRTUAL NETWORK | September 2020 | June 2023 | Allow | 33 | 1 | 0 | No | No |
| 17041943 | UNIFIED RESOURCE SCHEDULING COORDINATOR, METHOD FOR CREATING A VIRTUAL MACHINE AND/OR CONTAINER, AND UNIFIED RESOURCE SCHEDULING SYSTEM | September 2020 | August 2022 | Allow | 22 | 2 | 0 | No | No |
| 17018864 | OPERATOR MANAGEMENT APPARATUS, OPERATOR MANAGEMENT METHOD, AND OPERATOR MANAGEMENT COMPUTER PROGRAM | September 2020 | April 2023 | Allow | 32 | 1 | 0 | No | No |
| 17015377 | MEMORY BANDWIDTH THROTTLING FOR VIRTUAL MACHINES | September 2020 | December 2023 | Allow | 40 | 2 | 0 | Yes | No |
| 17011631 | USING VIRTUAL LOCAL AREA NETWORKS IN A VIRTUAL COMPUTER SYSTEM | September 2020 | September 2023 | Allow | 36 | 1 | 0 | Yes | No |
| 16984903 | Optimization of Parallel Processing Using Waterfall Representations | August 2020 | January 2023 | Allow | 29 | 1 | 0 | Yes | No |
| 16939617 | DATA PROCESSING UNIT FOR STREAM PROCESSING | July 2020 | March 2023 | Allow | 32 | 1 | 0 | No | No |
| 16914177 | METHODS, APPARATUS, AND SYSTEMS TO DYNAMICALLY SCHEDULE WORKLOADS AMONG COMPUTE RESOURCES BASED ON TEMPERATURE | June 2020 | December 2023 | Allow | 42 | 1 | 0 | No | No |
| 16954071 | VIRTUALIZED NETWORK FUNCTIONS | June 2020 | February 2023 | Allow | 32 | 2 | 0 | No | No |
| 16898300 | MIGRATION OF GUEST OPERATING SYSTEM OPTIMIZATION TOOL SETTINGS IN A MULTI-HYPERVISOR DATA CENTER ENVIRONMENT | June 2020 | August 2023 | Allow | 38 | 2 | 1 | Yes | No |
| 16887742 | PREDICTIVE SCHEDULING AND EXECUTION OF DATA ANALYTICS APPLICATIONS BASED ON MACHINE LEARNING TECHNIQUES | May 2020 | April 2023 | Allow | 35 | 1 | 0 | Yes | No |
| 16878238 | ADAPTIVE AND DISTRIBUTED TUNING SYSTEM AND METHOD | May 2020 | May 2023 | Abandon | 36 | 1 | 0 | No | No |
| 16869060 | EFFICIENT HANDLING OF NETWORK TOPOLOGY CHANGE NOTIFICATION FOR VIRTUAL MACHINES | May 2020 | April 2023 | Allow | 35 | 2 | 0 | Yes | No |
| 16861978 | VIRTUALIZED MOBILE OPERATING SYSTEM FOR MOBILE DEVICES FOR 5G OR OTHER NEXT GENERATION NETWORK | April 2020 | April 2023 | Allow | 35 | 1 | 0 | Yes | No |
| 16851231 | FLOW MANAGEMENT AND FLOW MODELING IN NETWORK CLOUDS | April 2020 | October 2023 | Abandon | 42 | 2 | 0 | No | No |
| 16838597 | METHOD FOR ACCESSING APPLICATION LOGS WITHIN VIRTUAL MACHINES BASED ON OPERATOR-DEFINED CRITERIA | April 2020 | April 2023 | Allow | 36 | 1 | 0 | Yes | No |
| 16838638 | GUEST CLUSTER DEPLOYED AS VIRTUAL EXTENSION OF MANAGEMENT CLUSTER IN A VIRTUALIZED COMPUTING SYSTEM | April 2020 | July 2023 | Allow | 39 | 2 | 0 | No | No |
| 16836847 | CLOUD-NATIVE PROXY GATEWAY TO CLOUD RESOURCES | March 2020 | December 2022 | Allow | 32 | 1 | 0 | Yes | No |
| 16835854 | TECHNIQUES TO MANAGE VIRTUAL CLASSES FOR STATISTICAL TESTS | March 2020 | October 2020 | Allow | 7 | 1 | 0 | Yes | No |
| 16820735 | OBJECT-BASED LOAD BALANCING APPROACHES IN DISTRIBUTED STORAGE SYSTEM | March 2020 | July 2022 | Allow | 28 | 1 | 0 | Yes | No |
| 16815162 | INTEGRATING VIRTUALIZATION AND HOST NETWORKING | March 2020 | February 2023 | Allow | 35 | 2 | 0 | Yes | No |
| 16808527 | JOB SCHEDULER, JOB SCHEDULE CONTROL METHOD, AND STORAGE MEDIUM | March 2020 | September 2022 | Allow | 31 | 1 | 0 | No | No |
| 16808143 | DATABASE SYSTEMS AND RELATED METHODS FOR VALIDATION WORKFLOWS | March 2020 | November 2021 | Allow | 20 | 1 | 0 | Yes | No |
| 16804085 | METHOD AND SYSTEM FOR EFFICIENT VIRTUAL MACHINE OPERATION WHILE RECOVERING DATA | February 2020 | June 2022 | Allow | 28 | 1 | 0 | No | No |
| 16803308 | VIRTUAL TRUSTED PLATFORM MODULES | February 2020 | June 2022 | Allow | 27 | 1 | 0 | Yes | No |
| 16803293 | VIRTUAL SERIAL PORTS FOR VIRTUAL MACHINES | February 2020 | May 2022 | Allow | 27 | 1 | 0 | No | No |
| 16801737 | FAST DEVICE DISCOVERY FOR VIRTUAL MACHINES | February 2020 | October 2022 | Allow | 31 | 1 | 0 | Yes | No |
| 16799582 | POWER AWARE LOAD PLACEMENT | February 2020 | September 2022 | Allow | 31 | 3 | 0 | Yes | No |
| 16796519 | DEEP LEARNING ARCHITECTURE FOR EDGE COMPUTING SYSTEM | February 2020 | November 2022 | Allow | 33 | 1 | 0 | Yes | No |
| 16791989 | SPECIAL CALLING SEQUENCE FOR CALLER-SENSITIVE METHODS | February 2020 | January 2022 | Allow | 23 | 4 | 0 | Yes | No |
| 16777263 | SYSTEM, METHOD AND RECORDING MEDIUM FOR TEMPERATURE-AWARE TASK SCHEDULING | January 2020 | February 2021 | Allow | 13 | 4 | 0 | Yes | No |
| 16743118 | LOAD BALANCING IN A HYPER-CONVERGED INFRASTRUCTURE (HCI) ENVIRONMENT | January 2020 | November 2022 | Allow | 34 | 2 | 0 | No | No |
| 16735195 | FUNCTION EXECUTION ENVIRONMENT SELECTION FOR DECOMPOSED APPLICATION | January 2020 | March 2023 | Allow | 38 | 4 | 0 | Yes | No |
| 16732547 | LPM MANAGEMENT USING CONTINGENT AND CONDITIONAL INPUTS | January 2020 | September 2022 | Allow | 32 | 2 | 0 | Yes | No |
| 16720717 | TASK SCHEDULING FOR MACHINE-LEARNING WORKLOADS | December 2019 | August 2022 | Allow | 32 | 1 | 0 | No | No |
| 16720385 | DISTRIBUTION OF APPLICATIONS AMONG MACHINES IN A CLOUD | December 2019 | May 2022 | Allow | 29 | 2 | 0 | Yes | No |
| 16712190 | HYPERVISOR SECURE EVENT HANDLING AT A PROCESSOR | December 2019 | July 2023 | Allow | 43 | 4 | 0 | Yes | No |
| 16707611 | APPLICATION-AWARE ANALYTICS FOR STORAGE SYSTEMS | December 2019 | February 2022 | Allow | 26 | 2 | 0 | Yes | No |
| 16698655 | CLIENT-SPECIFIED NETWORK INTERFACE CONFIGURATION FOR SERVERLESS CONTAINER MANAGEMENT SERVICE | November 2019 | April 2022 | Allow | 29 | 1 | 0 | Yes | No |
| 16692760 | SYSTEM AND METHOD FOR DISTRIBUTED EXECUTION OF A SEQUENCE PROCESSING CHAIN | November 2019 | October 2023 | Allow | 47 | 4 | 0 | Yes | No |
| 16691702 | INFORMATION PROCESSING DEVICE AND INFORMATION PROCESSING METHOD | November 2019 | July 2022 | Allow | 32 | 1 | 0 | No | No |
| 16671869 | SYSTEMS AND METHODS FOR VALIDATION OF ARTIFICIAL INTELLIGENCE MODELS | November 2019 | February 2023 | Allow | 39 | 0 | 0 | No | No |
| 16661016 | FUNCTION EXECUTION BASED ON DATA LOCALITY AND SECURING INTEGRATION FLOWS | October 2019 | February 2022 | Allow | 27 | 1 | 0 | No | No |
| 16660998 | APPARATUS AND METHOD FOR BATCH PROCESSING FOR BLOCKCHAIN TRANSACTIONS | October 2019 | October 2022 | Allow | 36 | 1 | 0 | No | No |
| 16593554 | Data Processing System with Consolidation of Virtual Machines and Host Server Standby and Power Up Functionality | October 2019 | January 2022 | Allow | 28 | 1 | 0 | Yes | No |
| 16587875 | CLOUD APPLICATION SCALER | September 2019 | September 2022 | Allow | 36 | 1 | 0 | No | No |
| 16587471 | EXTENDING SENSITIVE DATA TAGGING WITHOUT REANNOTATING TRAINING DATA | September 2019 | August 2022 | Allow | 35 | 1 | 0 | Yes | No |
| 16584584 | System and Method for Isolating Work within a Virtualized Scheduler Using Tag-Spaces | September 2019 | May 2022 | Allow | 32 | 2 | 0 | No | No |
| 16583242 | SYSTEM AND METHOD TO ANALYZE AND OPTIMIZE APPLICATION LEVEL RESOURCE AND ENERGY CONSUMPTION BY DATA CENTER SERVERS | September 2019 | January 2022 | Allow | 28 | 1 | 0 | No | No |
| 16566512 | SELF-PARTITIONING DISTRIBUTED COMPUTING SYSTEM | September 2019 | December 2021 | Allow | 27 | 1 | 0 | No | No |
| 16557110 | FORMATION FAILURE RESILIENT NEUROMORPHIC DEVICE | August 2019 | December 2022 | Allow | 39 | 1 | 0 | Yes | No |
| 16550602 | VIRTUALIZATION EXTENSION MODULES | August 2019 | December 2021 | Allow | 27 | 4 | 0 | Yes | No |
| 16545941 | Information Protection Method and Apparatus | August 2019 | December 2021 | Allow | 28 | 1 | 0 | No | No |
| 16540294 | SYSTEMS AND METHODS FOR AUTOMATED MONITORING AND TROUBLESHOOTING OF UNKNOWN DEPENDENCIES IN A VIRTUAL INFRASTRUCTURE | August 2019 | March 2022 | Allow | 31 | 1 | 0 | No | No |
| 16482313 | MANAGEMENT SYSTEM, MANAGEMENT APPARATUS, MANAGEMENT METHOD, AND PROGRAM | July 2019 | March 2022 | Allow | 32 | 2 | 0 | No | No |
| 16528461 | COLLABORATION ACROSS ISOLATED VIRTUAL ENVIRONMENTS | July 2019 | March 2022 | Allow | 31 | 2 | 0 | Yes | No |
| 16480669 | CREATING A DATA BACKUP OF A VIRTUALIZED AUTOMATION SOLUTION | July 2019 | January 2022 | Allow | 30 | 2 | 0 | No | No |
| 16521240 | Acceleration Capacity Adjustment Method and Apparatus for Adjusting Acceleration Capacity of Virtual Machine | July 2019 | March 2022 | Allow | 32 | 1 | 0 | No | No |
| 16511149 | ACCELERATING AND MAINTAINING LARGE-SCALE CLOUD DEPLOYMENT | July 2019 | August 2021 | Allow | 25 | 2 | 0 | Yes | No |
| 16512181 | SYSTEM RESOURCE COMPONENT UTILIZATION | July 2019 | August 2021 | Allow | 26 | 1 | 0 | Yes | No |
| 16502627 | VIRTUALIZING HARDWARE COMPONENTS THAT IMPLEMENT Al APPLICATIONS | July 2019 | October 2021 | Allow | 27 | 1 | 0 | No | No |
| 16454026 | MANAGING WORKLOADS OF A DEEP NEURAL NETWORK PROCESSOR | June 2019 | July 2022 | Allow | 36 | 3 | 0 | Yes | No |
| 16450811 | COMPUTING ON TRANSIENT RESOURCES | June 2019 | April 2022 | Allow | 34 | 2 | 0 | Yes | No |
| 16470076 | MANAGEMENT APPARATUS, MANAGEMENT SYSTEM, METHOD FOR CONTROLLING MANAGEMENT APPARATUS, AND PROGRAM | June 2019 | October 2021 | Allow | 28 | 1 | 0 | No | No |
| 16434817 | SMART REDUCE TASK SCHEDULER | June 2019 | March 2022 | Allow | 33 | 3 | 0 | Yes | No |
| 16424941 | RESOURCE AVAILABILITY-BASED WORKFLOW EXECUTION TIMING DETERMINATION | May 2019 | August 2021 | Allow | 27 | 1 | 0 | Yes | No |
| 16420071 | SCHEDULING OPERATIONS | May 2019 | September 2021 | Allow | 28 | 2 | 0 | No | No |
| 16413852 | Redistributing Workloads Across Worker Nodes Based on Policy | May 2019 | April 2021 | Allow | 23 | 1 | 0 | No | No |
| 16399187 | SYSTEM AND METHOD FOR PARALLEL SUPPORT OF MULTIDIMENSIONAL SLICES WITH A MULTIDIMENSIONAL DATABASE | April 2019 | November 2020 | Allow | 18 | 1 | 0 | No | No |
| 16386842 | SECURE SERVICE HOSTED IN A VIRTUAL SECURITY ENVIRONMENT | April 2019 | August 2020 | Allow | 16 | 2 | 0 | Yes | No |
| 16289479 | Composite Batching to Manage Throughput for Online Commerce Applications | February 2019 | June 2021 | Allow | 28 | 1 | 0 | Yes | No |
| 16287156 | ARITHMETIC AND LOGICAL OPERATIONS IN A MULTI-USER NETWORK | February 2019 | March 2021 | Allow | 25 | 1 | 0 | Yes | No |
| 16286084 | INTELLIGENT SERVER TASK BALANCING BASED ON SERVER CAPACITY | February 2019 | March 2021 | Allow | 24 | 1 | 0 | No | No |
| 16281984 | MANAGING CONTAINERS ACROSS MULTIPLE OPERATING SYSTEMS | February 2019 | September 2022 | Allow | 43 | 5 | 0 | Yes | No |
| 16281744 | Information Processing Device, Information Processing Method And Program | February 2019 | January 2021 | Allow | 22 | 2 | 0 | Yes | No |
| 16266144 | METHOD AND SYSTEM FOR SCHEDULING TRANSACTIONS IN A DATA SYSTEM | February 2019 | April 2021 | Allow | 26 | 3 | 0 | No | No |
| 16212510 | REMOTE WORKING SYSTEM AND WORKING METHOD THEREOF | December 2018 | October 2021 | Abandon | 35 | 2 | 0 | No | No |
| 16210016 | MEDIUM, CHANGE DETECTION METHOD, AND CHANGE DETECTION APPARATUS | December 2018 | April 2021 | Abandon | 28 | 1 | 0 | No | No |
| 16207504 | Method of Updating Application and Recording Medium | December 2018 | April 2021 | Abandon | 29 | 1 | 0 | No | No |
| 16205515 | CAPTURING TRACES OF VIRTUAL MACHINE OBJECTS COMBINED WITH CORRELATED SYSTEM DATA | November 2018 | July 2022 | Allow | 44 | 5 | 0 | Yes | No |
| 16206865 | HEALTH MONITORING FOR CLOUD COMPUTING PLATFORMS | November 2018 | September 2021 | Allow | 33 | 2 | 0 | Yes | No |
| 16199695 | OPTIMIZING INITIATOR ALLOCATION | November 2018 | January 2021 | Allow | 26 | 1 | 0 | No | No |
| 16193442 | MANAGEABLE EXTERNAL WAKE OF VIRTUAL MACHINES | November 2018 | October 2021 | Allow | 34 | 6 | 0 | Yes | No |
| 16182448 | Intelligently Scheduling Resynchronization Jobs in a Distributed Object-Based Storage System | November 2018 | February 2021 | Allow | 27 | 2 | 0 | Yes | No |
This analysis examines appeal outcomes and the strategic value of filing appeals for examiner TANG, KENNETH.
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 TANG, KENNETH works in Art Unit 2199 and has examined 434 patent applications in our dataset. With an allowance rate of 90.1%, this examiner has an above-average tendency to allow applications. Applications typically reach final disposition in approximately 32 months.
Examiner TANG, KENNETH's allowance rate of 90.1% places them in the 74% percentile among all USPTO examiners. This examiner has an above-average tendency to allow applications.
On average, applications examined by TANG, KENNETH receive 1.96 office actions before reaching final disposition. This places the examiner in the 44% 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 TANG, KENNETH is 32 months. This places the examiner in the 51% percentile for prosecution speed. Prosecution timelines are slightly faster than average with this examiner.
Conducting an examiner interview provides a +15.6% benefit to allowance rate for applications examined by TANG, KENNETH. This interview benefit is in the 55% 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, 32.8% of applications are subsequently allowed. This success rate is in the 71% 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 44.3% of cases where such amendments are filed. This entry rate is in the 69% percentile among all examiners. Strategic Recommendation: This examiner shows above-average receptiveness to after-final amendments. If your amendments clearly overcome the rejections and do not raise new issues, consider filing after-final amendments before resorting to an RCE.
When applicants request a pre-appeal conference (PAC) with this examiner, 112.5% result in withdrawal of the rejection or reopening of prosecution. This success rate is in the 81% 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 88.0% of appeals filed. This is in the 81% 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 frequently reconsiders rejections during the appeal process compared to other examiners. Per MPEP § 1207.01, all appeals must go through a mandatory appeal conference. Filing a Notice of Appeal may prompt favorable reconsideration even before you file an Appeal Brief.
When applicants file petitions regarding this examiner's actions, 62.1% are granted (fully or in part). This grant rate is in the 64% percentile among all examiners. Strategic Note: Petitions show above-average success regarding this examiner's actions. Petitionable matters include restriction requirements (MPEP § 1002.02(c)(2)) and various procedural issues.
Examiner's Amendments: This examiner makes examiner's amendments in 0.2% of allowed cases (in the 52% 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 17% 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.