I architect autonomous, stateful AI systems for high-compliance production environments. My work focuses on bridging the gap between Agentic Orchestration and Enterprise-Grade Infrastructure.

With 15+ years of experience in systems architecture, I specialize in transforming non-deterministic LLM outputs into reliable, mission-critical business workflows.

• AI Orchestration: LangGraph (Stateful Agents), CrewAI, Multi-Agent Swarms.
• LLMs & RAG: AWS Bedrock, OpenAI, Agentic RAG Optimization, pgvector.
• Infrastructure: Terraform, AWS (Fargate/ECS, Lambda, S3), Docker, Kubernetes.
• Observability: OpenTelemetry, LangSmith, Sentinel-AI Guardrails.
• Modern Stack: JavaScript (Node.js), TypeScript, Python, PostgreSQL.

I design cyclic, self-correcting agent loops that utilize Human-in-the-Loop (HITL) checkpoints. This ensures that AI agents remain grounded and accountable in financial and clinical environments.

Expertise in building AI Gateways for real-time PII redaction and sensitive data masking, ensuring that production AI implementations meet HIPAA and SOC2-level standards.

I leverage OpenTelemetry for system-level health (latency/throughput) and LangSmith for logic-level tracing (evaluating reasoning chains and reducing hallucinations).

• the-rcm-guardian: Agentic RCM service using LangGraph, Multimodal Vision, and LIMS reconciliation. Features HITL checkpoints and pgvector RAG.
• agentic-deep-research-graph: Self-correcting multi-agent research loop using LangGraph and GPT-4o. Demonstrates stateful orchestration and adaptive search.
• sentinel-ai-gateway: Privacy-first AI Proxy for PII redaction and enterprise observability (OTel/LangSmith) in production LLM workflows.
• clinical-intelligence-rag: Complex RAG pipelines for regulated healthcare data.

• Location: Austin, TX (USA)
• LinkedIn: pvenkata-tech
• Focus: Autonomous Agents, Distributed Systems, and AI Governance.

"Building the infrastructure that allows AI to move from experimental chats to autonomous production systems."