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ananthasharma/README.md

Anantha Sharma

AI strategy, enterprise architecture, and applied research leader focused on building governed, production-grade AI systems for regulated industries.

I work at the intersection of:

  • Enterprise AI strategy and architecture
  • Agentic AI and trustworthy multi-agent systems
  • Domain-aligned RAG and semantic data preparation
  • Ontology-grounded vocabulary registries
  • Privacy-preserving AI and data governance
  • Model risk, AI reliability, and compliance automation
  • Financial services technology transformation

Recent research includes:

  • Trustworthy Multi-Agent Systems: Mitigating Semantic Drift with the Argent Signaling Protocol
  • Ontology-Grounded Semantic Vocabulary Registry for Domain-Aligned RAG
  • Privacy-preserving systems, hallucination detection, synthetic data, and AI governance

Selected interests:

  • Agentic AI operating models
  • Semantic routing and ontology-grounded retrieval
  • AI governance for regulated enterprises
  • Data lineage, model lineage, and MLOps
  • Applied AI architecture for financial services

Links:

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  1. argent-signaling-protocol argent-signaling-protocol Public

    Argent Signaling Protocol: auditable quality signals for trustworthy multi-agent AI systems and semantic drift mitigation.

    Python

  2. argent-framework argent-framework Public

    A governance-first reference repository for composing, orchestrating, and auditing enterprise AI agents.

    Python