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AI Strategy & Engineering

AI Systems I've Built

Production-grade AI systems for regulated industries: multi-agent orchestration, workflow automation, and compliance-aware tools that reduce manual effort while maintaining audit trails.

Multi-Agent Systems
RAG
LLMs
Python
React
Claude Agent SDK
MCP

What I Focus On

Building AI systems that work reliably at scale, with a focus on practical value.

Multi-Agent Workflows

Orchestrating specialized agents through defined phases (Plan, Build, Test, Review, Document) with intelligent model routing and pattern matching for consistent, auditable outputs.

Workflow Automation

Building tools that eliminate manual work: timeline conversion, document processing, and data transformation that save 3-5 hours per project while reducing errors.

Compliance-Aware AI

AI systems designed for pharma and MedComms: MLR-aligned screening, audit trails, and governance frameworks that meet regulatory expectations from the start.

How I Work With Teams on AI

A collaborative approach focused on delivering practical value.

1

Understand the Problem

Deep dive into current workflows, pain points, and compliance requirements, understanding the manual work that consumes team time.

2

Design the Architecture

Map out agent roles, data flows, and integration points. Define phases, model routing, and governance frameworks.

3

Build & Iterate

Rapid prototyping with frequent feedback loops, ensuring alignment with team needs.

4

Deploy & Monitor

Production deployment with logging, error handling, audit trails, and performance monitoring for regulated environments.

Interested in AI Strategy?

Let's discuss how AI can solve your team's challenges.