MEMORY
Episodic, semantic, graph and working memory—retrieved with purpose, not dumped into context.
AGENTIC AI ENGINEER // SYSTEM ONLINE
Memory, governance and self-improving systems for agents that work in the real world.

I design the machinery between a model and the real world—the context it receives, the tools it can touch, the evidence it leaves, and the lessons it is allowed to keep.
Episodic, semantic, graph and working memory—retrieved with purpose, not dumped into context.
Policy gates, approval boundaries, provenance, and review-before-apply learning.
Trace-level evidence, deterministic checks, failure taxonomies, and improvement loops.
Multi-agent workflows that survive long tasks, retries, handoffs, and real infrastructure.
A multi-agent anomaly detection system for a multimillion-dollar dairy company—built to find where subtle quality anomalies were hiding across a vast collection network.
Selected open-source systems from my GitHub. Each begins with the same question: what does an agent need around the model to become reliable?
A local-first self-improvement harness that turns agent traces into governed evaluations, memories, skills, and fine-tuning exports.
↗02LangGraph orchestration with durable memory, hybrid retrieval, local embeddings, injection defense, and evidence-first execution.
↗03Four-tier retrieval across SQLite FTS5, a knowledge graph, vectors, and an LLM agent—exposed through MCP.
↗04An agent-navigated local knowledge base for persistent memory across Claude Desktop, LM Studio, and ChatGPT.
↗05A weather-market agent that fuses forecast sources, finds mispriced contracts, and sizes risk using the Kelly criterion.
↗Building persistent memory, governed learning, and multi-agent infrastructure for enterprise systems.
Worked on Hindi and English evaluation and training for multilingual voice intelligence.
Built an anomaly-detection system across 142K+ dairy records; two of three randomly audited flagged centers were confirmed.
Helped grow a 100K+ YouTube audience, produced a podcast with 2M+ listens, and hosted large-scale hackathons.
THE FUTURE ISN’T JUST
BIGGER MODELS.
Have an agent system that needs memory, governance, evaluation—or a path out of prototype purgatory?