Hi, I'm Premkumar Kora

Principal AI Architect | Generative AI Strategist | Published Author

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Executive Summary

As a Principal AI Architect, PMP-Certified and MBA, I offer a rare combination: 6+ years of cutting-edge Generative AI specialization built on a foundation of 25+ years of Enterprise Engineering & Leadership. I bridge the dangerous gap between "Business Strategy" and "Technical Execution." While others prototype concepts, I translate ambiguous business requirements into high-performance, autonomous AI systems that deliver measurable ROI. I specialize in designing Enterprise Agentic Workflows, Secure RAG Systems, and Multi-Agent Orchestration for regulated industries (Insurance, Healthcare, Finance).

Currently, I focus on translating ambiguous business requirements into scalable AI solutions that deliver tangible ROI, ensuring data sovereignty and regulatory compliance.

Strategic Impact & ROI

• $1.8M Claims Automation: Architected an Agentic AI platform on AWS (Claude/Titan) that autonomously processes 80% of claims, reducing cycle time from 5.2 to 1.1 days.
• $1.0M Cost Avoidance: Engineered a secure RAG application for policy analysis, eliminating 100% of manual data capture for adjusters.
• 85% Efficiency Gain: Deployed a Multi-Agent GenAI platform unifying 52 reporting systems, saving $340K annually.

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Architectural Specialization: Agentic Systems

Below is a high-level representation of the Agentic AI Data Cleaning and Clustering Architecture I designed, utilizing Multi-Agent Orchestration

Below is a high-level representation of the Agentic Claims Processing Architecture I designed, utilizing Multi-Agent Orchestration to handle complex decision-making logic.

%%{
  init: {
    'theme': 'base',
    'themeVariables': {
      'primaryColor': '#BB2588',
      'primaryTextColor': '#fff',
      'primaryBorderColor': '#7C0000',
      'lineColor': '#F8F9FA',
      'secondaryColor': '#006100',
      'tertiaryColor': '#fff'
    }
  }
}%%

graph TD
    %% --- Define Classes ---
    classDef liquidStart fill:#000000,stroke:#333,stroke-width:4px,color:#fff
    classDef liquidAgent fill:#8E2DE2,stroke:#4A00E0,stroke-width:2px,color:#fff
    classDef liquidModel fill:#F80759,stroke:#BC4E9C,stroke-width:2px,color:#fff
    classDef liquidData fill:#00F260,stroke:#0575E6,stroke-width:2px,color:#000

    %% --- Nodes ---
    Input(["Claims Documents"])
    
    subgraph Orchestration [" Multi-Agent Orchestrator "]
        direction TB
        Router{{" Router Agent "}}
        
        subgraph Specialist_Agents [" Specialist Agents (CrewAI) "]
            Policy[("Policy RAG ")]
            Fraud[("Fraud Detection ")]
            Medical[("Medical Encoder ")]
        end
    end

    LLM["AWS Bedrock (Claude 3.5) "]
    Decision{{"Decision Engine "}}
    Output(["Approved/Rejected"])

    %% --- Connections ---
    Input --> Router
    Router -- "Context Retrieval" --> Policy
    Router -- "Risk Analysis" --> Fraud
    Router -- "Entity Extraction" --> Medical
    
    Policy -.-> LLM
    Fraud -.-> LLM
    Medical -.-> LLM
    LLM ==> Decision
    Decision --> Output

    %% --- Apply Styles ---
    class Input,Output liquidStart
    class Router,Decision liquidAgent
    class Policy,Fraud liquidData
    class Medical,LLM liquidModel

    %% --- Link Styling (Simplified) ---
    linkStyle default stroke:#BB2588,stroke-width:2px,fill:none

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