This portfolio reflects a long-running research-to-IP agenda across enterprise AI, sustainable software, AI reliability, NLP, software intelligence, decision intelligence, and emerging technology adoption. The emphasis is on building reusable technology assets that translate research ideas into enterprise-scale systems, standards, and operational capabilities.  

AI Cost Optimization, Sustainable AI, Green Software & ESG

These inventions address the environmental and economic footprint of AI and digital systems. The portfolio covers resource allocation, ESG-optimized decisioning, energy-aware computing, prompt and context optimization, and sustainability-oriented optimization for emerging software and AI infrastructures. This category directly aligns with enterprise needs to govern AI cost, energy, carbon, and operational impact as measurable engineering constraints rather than after-the-fact reporting concerns.

Patent families / representative filings.

• • System and Method for ESG Reporting based Optimized Resource Allocation Across ESG Dimensions. US-12393459-B2; 18/079,182 (Issued: Aug 19, 2025)

  • Systems and Methods for Managing Energy Consumption and Carbon Emissions in Artificial Intelligence (AI) Applications. US 19/287,326 (Filed: Jul 31, 2025)

  • Computer Implemented Method and System for Prompt Processing. US 19/233712 (Filed: Jun 10, 2025)

  • System and a Method for Energy Efficient Irrelevant Context Identification in LLM Inputs. IN 202411048712 (Filed: Jun 25, 2024)

  • Providing Energy Efficient Dynamic Redundancy Elimination for Stored Data. US-11989210-B2; 17/812,028 (Issued: May 21, 2024)

  • Sustainability-Based Computing Resource Allocation. US-11714688-B1; 18/056,400 (Issued: Aug 1, 2023)

  • Energy Efficient Collaboration for Environmental Social and Governance (ESG) Data Consolidation and Validation in the Metaverse. US 18/081,264 (Filed: Dec 14, 2022)

  • Energy Cost Reduction of Metaverse Operations. US 17/942,875 (Filed: Sep 12, 2022)

AI Reliability, Testing, Evaluation & Data Quality

These inventions address the reliability of AI-enabled and data-driven systems by focusing on perturbation testing, test-data generation, performance-impact analysis, defect and test analytics, and irregularity-aware machine learning. The portfolio positions reliability, evaluation, data quality, and operational robustness as measurable engineering concerns, which is central to moving enterprise AI from experimentation to production-grade deployment.

Patent families / representative filings.

• Learning Based Incident or Defect Resolution, and Test Generation. IN 526137 (Issued: Mar 14, 2024), US 11233693 B2 (Issued: Jan 25, 2022), US 10771314 B2 (Issued: Sep 1, 2020)

• Generating Test Data from Samples using Natural Language Processing and Structure-Based Pattern Determination. IN 425527 (Issued: Mar 16, 2023), US 10204032 B2 (Issued: Feb 12, 2019), EU EP3249547 A1 (Filed: Apr 6, 2017)

• Natural Language Dialogue System Perturbation Testing. US-11416556-B2; 11416556 A1 (Issued: Aug 16, 2022)

• Machine Learning Based Quantification of Performance Impact of Data Irregularities. US 11210471 B2 (Issued: Dec 28, 2021)

• Using Similarity Analysis and Machine Learning Techniques to Manage Test Case Information. US 10768893 B2 (Issued: Sep 4, 2020), AU 2018264047 (Filed: Nov 14, 2018), US 15/818,456 (Filed: Nov 1, 2017)

• Constraint Extraction from Natural Language Text for Test Data Generation. CA 2945458 (Issued: Mar 10, 2020), US 10031839 B2 (Issued: Jul 24, 2018), AU 2016247156 (Issued: May 1, 2017)

• Software Testing Using Artificial Intelligence Techniques. IN 201741001446 (Filed: Jan 13, 2017)

Enterprise AI Operations, Application Management & Operational Intelligence

These inventions focus on applying AI, learning-based methods, and operational analytics to improve enterprise application management, competency analysis, anticipatory sample analysis, and trade-off resolution. This category shows the ability to identify recurring enterprise technology pain points and convert them into scalable AI-enabled operational capabilities that improve productivity, reduce expert dependence, and support more intelligent technology service delivery.

Patent families / representative filings.

• Continuous Learning Based Application Related Trade-off Resolution and Implementation. US-11972251-B2; 17/236,841 (Issued: Apr 30, 2024)

• System Behavior Profiling-Based Dynamic Competency Analysis. US-11630641-B2; 17/157,599 (Issued: Apr 18, 2023)

• Anticipatory Sample Analysis for Application Management. IN 401142 (Issued: Jul 11, 2022), US 10169330 B2 (Issued: Jan 1, 2019)

NLP, Information Retrieval, Requirements & Enterprise Text Intelligence

These inventions address the challenge of extracting structured meaning, relevance, intent, entities, constraints, and relationships from natural language text. The portfolio covers entity disambiguation, semantic clustering, query expansion, text prioritization, information extraction, type inference, and requirements intelligence, reflecting a long-running ability to translate NLP research into enterprise-grade systems for search, discovery, automation, and decision support.

Patent families / representative filings.

• Type Inference from Natural Language Text Data. IN 417322 (Issued: Jan 9, 2023), US 9880997 B2 (Issued: Jan 30, 2018)

• Input Entity Identification from Natural Language Text Information. IN 399778 (Issued: Jun 22, 2022), AU 2016269573 (Issued: Apr 11, 2018), US 9817814 B2 (Issued: Nov 1, 2017)

• Entity Disambiguation in Natural Language Text. IN 395894 (Issued: Apr 29, 2022), US 9245015 B2 (Issued: Jan 26, 2016)

• Automatic Prioritization of Natural Language Text Information. IN 393570 (Issued: Mar 30, 2022), US 10002188 B2 (Issued: Jun 19, 2018)

• Natural Language Text Based Insight Disambiguation. IN 201741022771 (Filed: Jun 29, 2017)

• User-Guided Search Query Expansion. US 9501559 B2 (Issued: Nov 22, 2016)

• Grouping Semantically Related Natural Language Specifications of System Requirements into Clusters. US 9454602 B2 (Issued: Sep 26, 2016)

Software Architecture, Source-Code Intelligence & Cloud Modernization

These inventions focus on understanding, governing, and transforming complex enterprise software estates through source-code diagnostics, component discovery, migration context, flow-graph-based controls, collective portfolio migration, and collaborative cloud migration. This category aligns with enterprise needs to modernize legacy systems by making architecture, dependency structure, transformation risk, and migration opportunity more visible, measurable, and actionable.

Patent families / representative filings.

• Component Discovery from Source Code. IN 335860 (Issued: Apr 23, 2020), US 9836301 B2 (Issued: Dec 5, 2017), US 9323520 B2 (Issued: Apr 26, 2016), US 8881104 B2 (Issued: Nov 4, 2014), EU 13001439.2 (Filed: Mar 20, 2013)

• Migration Context and Flow Graph Based Migration Control. EP4163789A1; 22186245.1 (Issued: Jul 16, 2025), US-11778054-B2; 17/495553 (Issued: Oct 17, 2023)

• Collective Application Portfolio Migration Control. US-12131198-B2; 17/673,615 (Issued: Oct 29, 2024)

• Collaborative Learning-Based Cloud Migration Implementation. US-11789633-B2; 17/812,028 (Issued: Oct 17, 2023), IN 202211010169 (Filed: Feb 25, 2022)

Machine Learning Enablement, Semantic Analytics & AutoML Support

These inventions enhance the core pipelines of applied machine learning through semantic matching, feature extraction, structural-hole identification, technique recommendation, and feature-relevance scoring. This category demonstrates the ability to turn ML expertise into reusable enablement capabilities that reduce manual modeling effort, improve solution design quality, and help enterprises make more consistent AI and analytics decisions.

Patent families / representative filings.

• Machine Learning Based Semantic Structural Hole Identification. US-11893503-B2; 16/594,899 (Issued: Feb 6, 2024)

• Continuous Learning Enabled Semantic Matching of Text Samples. IN 468167 (Issued: Nov 10, 2023), US 10409914 B2 (Issued: Sep 10, 2019), AU 2018278988 (Issued: Sep 17, 2017)

• Feature Extraction for Machine Learning. IN 443042 (Issued: Aug 4, 2023), US 10565520 B2 (Issued: Feb 18, 2020), IN 201741019972 (Filed: Jun 7, 2017)

• Recommending Machine Learning Techniques, Features, and Feature Relevance Scores. US-11361243-B2; 11361243 (Issued: Jun 14, 2022)

Agentic AI, Automation Selection & Compliance-Aware Control

These inventions connect natural language understanding, semantic scoring, advisory agents, automation selection, and regulatory variation analysis with the control of software or robotic agents. The portfolio is strategically relevant to enterprise AI because agentic and automated systems require governance-aware control mechanisms, explainable selection logic, and adaptation to business, regulatory, and operational constraints rather than unconstrained automation.

Patent families / representative filings.

• Natural Language Unification Based Robotic Agent Control. IN 506087 (Issued: Feb 1, 2024), US 11062142 B2 (Issued: Jul 13, 2021)

• Natural Language Eminence Based Robotic Agent Control. IN 501202 (Issued: Jan 19, 2024), US 10824870 B2 (Issued: Nov 3, 2020)

• Temporal Variation Identification Of Regulatory Compliance Based Robotic Agent Control. US 11213948 B2 (Issued: Jan 4, 2022)

• Using Natural Language Processing and Similarity Analysis Techniques to Select a Best-Fit Automation Service. US 11282014 B2 (Issued: Mar 22, 2022), IN 201741018382 (Filed: May 25, 2017)

• Design of a Continuously Learning Intelligent Advisory Agent to Formulate Buy vs. Build Equation. IN 202011030399 (Filed: Jul 16, 2020)

Computational Social Intelligence, Trend Mining & Digital Ecosystem Analytics

These inventions address the extraction of trends, signals, cascading effects, semantic patterns, and social insight from large-scale natural language and digital ecosystem data. This category shows the ability to define AI directions that go beyond automation and support strategic sensing of emerging concerns, stakeholder behavior, public discourse, digital-world dynamics, and complex socio-technical systems.

Patent families / representative filings.

• Identifying Trends Associated with Topics from Natural Language Text. IN 507852 (Issued: Feb 6, 2024), US 10157223 B2 (Issued: Dec 18, 2018), AU 2017201629 (Issued: May 31, 2018)

• Temporal Impact Analysis of Cascading Events on Metaverse-Based Organization Avatar Entities. US-12229902-B2; 17/987,281 (Issued: Feb 18, 2025)

• Data-driven Social Media Analytics Application Synthesis. US-11847417-B2; 17/200,469 (Issued: Dec 9, 2023)

Enterprise Security, Policy Monitoring & Threat Management

These inventions strengthen enterprise defence mechanisms through collaborative monitoring, policy-violation detection, probabilistic modeling, and adaptive learning for threat management. This category is relevant to AI leadership because enterprise AI and automation systems increasingly operate in security-sensitive environments where policy compliance, monitoring, anomaly detection, and adaptive risk response must be built into the architecture from the beginning.

Patent families / representative filings.

• Adaptive Learning for Enterprise Threat Management. US 20100007489 A1 (Filed: Jul 1, 2008)

• Probabilistic Modeling of Collaborative Monitoring of Policy Violations. US 20100010776 A1 (Filed: Jul 1, 2008)

• System and Method for Collaborative Monitoring of Policy Violations. US 12/057855 (Filed: Mar 1, 2008)

Quantum Computing & Emerging Technology Decision Support

This invention addresses the practical enterprise question of when a problem is better suited for quantum computing versus classical computing, using NLP similarity matching and decision-support logic. The category is intentionally kept separate because it signals future-facing technology judgment: the ability to evaluate emerging technologies through a business-relevant lens and help enterprises avoid hype-driven adoption while identifying where new computing paradigms may create genuine technical or economic advantage.

Patent families / representative filings.

• Utilizing Natural Language Processing Similarity Matching to Determine Whether a Problem Requires Quantum Computing OR Classical Computing. US-12346825-B2; 17/107,357 (Issued: Jul 1, 2025), IN 202041021399 (Filed: May 21, 2020)