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Research Hub
A central research catalog organized by domain with publication, repository, dataset, and framework linkages.
Designing enterprise-scale AI systems that connect decision services, operating models, and measurable business outcomes.
Related publications: Enterprise Intelligence Framework™: A Reference Framework for Connecting Executive Intent, Control Architecture, Operating Models, and Platform Delivery; Enterprise Digital Brain An AI-Augmented System for Knowledge Organization and Cognitive Productivity
Related GitHub repositories: research-portfolio; RakeshKumarAgrawal.github.io
Related datasets: BQEB ForecastBench
Related frameworks: Enterprise Digital Brain; Enterprise Intelligence Framework™
Expand enterprise AI reference architecture patterns across additional domains.
Building governance models that link AI policy, controls, evidence, and accountability across the lifecycle.
Related publications: Enterprise AI Governance Framework™: A governance reference model connecting policy, controls, evidence, review, escalation, and lifecycle accountability; Enterprise Intelligence Framework™: A Reference Framework for Connecting Executive Intent, Control Architecture, Operating Models, and Platform Delivery
Related GitHub repositories: research-portfolio
Related datasets: None linked yet
Related frameworks: Enterprise Intelligence Framework™
Formalize governance KPIs for model risk and policy adherence.
Researching platform operating models that improve delivery resilience, developer productivity, and lifecycle governance.
Related publications: Enterprise Intelligence Framework™: A Reference Framework for Connecting Executive Intent, Control Architecture, Operating Models, and Platform Delivery; Digital Brain for IT Operations and Observability: An AI-Augmented Cognitive Framework for Incident Intelligence
Related GitHub repositories: RakeshKumarAgrawal.github.io; research-portfolio
Related datasets: BQEB ForecastBench
Related frameworks: Enterprise Intelligence Framework™; Enterprise Digital Brain
Document internal platform maturity dimensions for AI-enabled delivery systems.
Exploring cloud-native architectures for scalable AI delivery, observability, and data-intensive workloads.
Related publications: Digital Brain for IT Operations and Observability: An AI-Augmented Cognitive Framework for Incident Intelligence; BQEB ForecastBench: Benchmarking AI Models for Smart Grid Forecasting Using BQEB-Data v1
Related GitHub repositories: RakeshKumarAgrawal.github.io; Rakesh-K-Agrawal
Related datasets: BQEB-Data BIO-Quantum Energy Brain Benchmark Dataset for Smart Grid Intelligence, Renewable Forecasting, Storage Optimization, and Cyber Resilience; BQEB-Data: An Open Benchmark Dataset for Autonomous Energy Intelligence and Smart Grid Analytics
Related frameworks: BQEB-Data; BQEB ForecastBench
Expand reference workload patterns for secure multi-cloud AI systems.
Developing structured knowledge architectures that improve enterprise memory, retrieval, and decision coherence.
Related publications: Enterprise Digital Brain An AI-Augmented System for Knowledge Organization and Cognitive Productivity; Enterprise Intelligence Framework™: A Reference Framework for Connecting Executive Intent, Control Architecture, Operating Models, and Platform Delivery
Related GitHub repositories: research-portfolio
Related datasets: None linked yet
Related frameworks: Enterprise Digital Brain; Enterprise Intelligence Framework™
Evaluate graph-based enterprise knowledge models for reasoning support.
Advancing explainable and edge-enabled healthcare AI systems for patient monitoring and disease risk prediction.
Related publications: BioBrain: An Explainable Federated AI Framework for Multi-Omics Disease Risk Prediction in Life Science; Smart ICU Monitoring System Using IoT and Edge AI for Real-Time Patient Risk Prediction; +1 more
Related GitHub repositories: research-portfolio
Related datasets: None linked yet
Related frameworks: BioBrain
Extend multimodal healthcare signal fusion for interpretable risk scoring.
Designing AI-assisted decision systems that integrate evidence, uncertainty, and operational context.
Related publications: Enterprise Intelligence Framework™: A Reference Framework for Connecting Executive Intent, Control Architecture, Operating Models, and Platform Delivery; BQEB ForecastBench: Benchmarking AI Models for Smart Grid Forecasting Using BQEB-Data v1
Related GitHub repositories: research-portfolio; RakeshKumarAgrawal.github.io
Related datasets: BQEB ForecastBench
Related frameworks: Enterprise Intelligence Framework™; BQEB ForecastBench
Expand decision model evaluation templates for executive governance contexts.
Structuring responsible AI methods for transparency, governance, and reliability in enterprise deployments.
Related publications: Enterprise AI Governance Framework™: A governance reference model connecting policy, controls, evidence, review, escalation, and lifecycle accountability; LLMOps Maturity Model™: A maturity model for progressing from experimental LLM use to resilient, governed, observable, and scalable operations
Related GitHub repositories: research-portfolio
Related datasets: None linked yet
Related frameworks: Enterprise Intelligence Framework™
Publish responsible AI control mappings for enterprise lifecycle checkpoints.
Researching governed agentic systems with bounded autonomy, human oversight, and operational safeguards.
Related publications: Agentic Enterprise Blueprint™: A blueprint for introducing governed agentic systems into enterprise workflows with bounded autonomy and human oversight
Related GitHub repositories: research-portfolio; Rakesh-K-Agrawal
Related datasets: None linked yet
Related frameworks: Agentic Enterprise Blueprint™; Enterprise Digital Brain
Define runtime guardrail patterns for multi-agent enterprise orchestration.
Developing observability approaches for AI services across incidents, drift, and operational intelligence.
Related publications: Digital Brain for IT Operations and Observability: An AI-Augmented Cognitive Framework for Incident Intelligence; LLMOps Maturity Model™: A maturity model for progressing from experimental LLM use to resilient, governed, observable, and scalable operations
Related GitHub repositories: RakeshKumarAgrawal.github.io; research-portfolio
Related datasets: BQEB ForecastBench
Related frameworks: Enterprise Digital Brain
Expand AI reliability signal taxonomy for cross-platform observability.
Establishing operational maturity models for reliable, scalable, and governed LLM deployment pipelines.
Related publications: LLMOps Maturity Model™: A maturity model for progressing from experimental LLM use to resilient, governed, observable, and scalable operations; Agentic Enterprise Blueprint™: A blueprint for introducing governed agentic systems into enterprise workflows with bounded autonomy and human oversight
Related GitHub repositories: research-portfolio; RakeshKumarAgrawal.github.io
Related datasets: None linked yet
Related frameworks: Agentic Enterprise Blueprint™; Enterprise Intelligence Framework™
Publish lifecycle controls for evaluation, release, and rollback of LLM services.
Let's discuss research collaborations, enterprise AI strategy, platform engineering, open science initiatives, or speaking opportunities.