Max Boving.

Personal portfolio / 2026

Portrait

Education

B.S. in Information Sciences
Emphasis in Data Science
Minor in Business Administration

About

About Max Boving

I’m an AI and data engineer who enjoys turning complex, messy problems into systems people can actually use.

My work spans data science, software engineering, and applied AI. I’ve built predictive models, RAG systems, analytics platforms, data pipelines, and APIs across legal education, environmental research, and business analytics. I’m especially drawn to projects where I can work closely with users, understand how they operate, and translate their needs into a practical technical solution.

Recently, I helped build data infrastructure supporting more than 80 million environmental sensor records, developed tariff simulations for supplier decision-making, and led the development of an academic analytics platform deployed at the University of Arizona. I’m also exploring how AI can model human behavior and population differences through my work on OptoJury.

I’m most interested in forward-deployed engineering, data science, and applied AI roles where I can combine technical ownership with product thinking, client collaboration, and real-world problem solving.

Projects

CEO Intelligence Assistant
AgenticMIND RAG assistant generating a revenue model with flagged assumptions

agenticMIND is a CEO-facing assistant for turning company information into reports, explanations, and next steps that can be checked.

  • Connected documents and company context through retrieval, then added typed routing for reports, explanations, briefings, and planning.
  • Built the FastAPI and React system with SQLite persistence, trace metadata, document ingestion, and generated artifacts so users could see and keep the result.
Environmental Data & AI Platform

Biosphere 3 is a digital operating layer for Biosphere 2, connecting environmental telemetry, research data, dashboards, agentic analysis, and a future 3D digital twin. I owned the technical work end to end across frontend, backend, pipelines, clustering, RAG, and infrastructure.

  • Built a timeline-first PostgreSQL warehouse and Oracle-to-PostgreSQL pipelines, migrating roughly 3.2 GB of telemetry into a system with sub-100ms query performance.
  • Built the React/Vite and Astro frontends, FastAPI services, biome RAG and clustering prototypes, local Ollama/Qwen gateway, Minds APIs, and JetStream/Ansible environment.
Autonomous Agentic Trading Bot
Paper trading portfolio showing a balance of $10,770.36Paper trading ↗

ClawdTrader is a scheduled, agentic trading loop I built to explore how a group of specialized tools could support paper-trading decisions without putting real money at risk. The system could research a market, generate questions, manage a watchlist, and use those pieces of context to shape the next decision.

  • Defined a custom SDK and connected the agents to Alpaca’s paper-trading API over MCP, giving the system a structured way to inspect markets and place simulated trades.
  • Built reusable components for deep research, question generation, watchlist management, and agent coordination so the loop could move from investigation to action on a schedule.
AI Surf Technique Coach
SurfBuddy surf technique coaching interface

SurfBuddy is a video-based surf coach. A user uploads footage of a maneuver, and the system compares their movement with reference technique before an LLM turns the analysis into useful coaching feedback.

  • Built upload and frame-selection flows, then used MediaPipe, OpenCV, and 3D pose landmarks to analyze joints, stance, camera angle, and body position.
  • Compared user and reference poses, then passed the results to an OpenAI-powered coach that explains the movement and suggests drills.