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Naveen Kumar Baskaran

Senior SAP Developer & AI/ML Engineer at SAP Labs India | PhD Candidate (ML & Photonics)

Building production-grade Agentic AI solutions for enterprise SAP workflows β€” LLM-powered agents integrated with SAP Joule, deployed on Kubernetes (Kyma).


πŸ† Achievements


πŸ“¦ Published Packages

PyPI

codewise-ai consync mcp-a2a-bridge tokmon-ai promptlab-ai

npm

@nkbai/codewise @nkbai/consync @nkbai/tokmon @nkbai/promptlab

Docker Hub

mcp-a2a-bridge tokmon agent-gateway

GitHub Actions Marketplace

Codewise PR Review AI Conflict Resolver

Homebrew

brew install naveenkumarbaskaran/tap/codewise
brew install naveenkumarbaskaran/tap/consync
brew install naveenkumarbaskaran/tap/mcp-a2a-bridge
brew install naveenkumarbaskaran/tap/tokmon
brew install naveenkumarbaskaran/tap/promptlab

πŸ”§ What I Build

  • πŸ—οΈ Agent Architecture β€” PEOS (Planner-Executor-Observer-Synthesiser) patterns for multi-step enterprise automation
  • ⚑ Token Optimization β€” Dynamic tool binding, history windowing, result truncation (60-80% cost reduction)
  • πŸ”Œ SAP + AI Integration β€” 20+ OData API integrations with error sanitization and scorecard compliance
  • 🌐 Protocol Bridges β€” MCP ↔ A2A interoperability for multi-agent ecosystems
  • πŸ”¬ Research β€” Swarm intelligence, CNN hyperparameter optimization, optical biosensors in ML

πŸ› οΈ Tech Stack


πŸ“Š GitHub Stats


πŸ“š Publications & Patents

  • Hyperparameter Tuning of CNNs using Nature-Inspired Metaheuristic Algorithms (IEEE)
  • Optical Biosensors in ML Applications
  • Swarm Intelligence for Multi-Agent Coordination
  • Patent: Implicitly Presenting Information of User's Point of Interest

πŸ”— Connect

LinkedIn Medium Portfolio IEEE PyPI Docker Hub

Pinned Loading

  1. AdaptiveCruiseControl AdaptiveCruiseControl Public

    My Summer Project 2017

    C++ 2 1

  2. A2A-Kit A2A-Kit Public

    Agent-to-Agent protocol toolkit for multi-agent communication and discovery

    Python

  3. AgentForge AgentForge Public

    Production-grade enterprise AI agent framework β€” PEOS orchestration, 77% token savings, zero error leaks. Built for Monday morning traffic, not weekend demos.

    Python

  4. mcp-a2a-bridge mcp-a2a-bridge Public

    Bidirectional MCP ↔ A2A bridge β€” connect any MCP tool server to the A2A agent ecosystem (and vice versa) with one command. The answer to MCP vs A2A is both.

    Python

  5. NeuralHive NeuralHive Public

    Swarm intelligence framework for multi-agent LLM collaboration β€” emergent problem-solving through agent coordination.

    Python

  6. TokenShield TokenShield Public

    LLM token optimization toolkit β€” dynamic tool binding, history windowing, result truncation. Cut your AI agent costs by 60-80%.

    Python