Shipped flagship
Maintenance-Eye
Multimodal maintenance copilot with live audio, camera input, backend tools, deployment, and tests.
Google ADK, Gemini Live API, FastAPI, Firestore, Cloud Run
Applied AI Engineer
Applied AI Engineer building multimodal agents and LLM systems for operational workflows.
I build production-minded AI systems where models are one part of a working product: real-time interfaces, backend tools, retrieval, confirmations, deployment, and tests.
My strongest public proof is Maintenance-Eye, a deployed maintenance copilot using Google ADK, Gemini Live API, FastAPI, Firestore, and Cloud Run. GovtIntel is my second current project, kept clearly in progress until the RAG demo and evaluations are complete.
- Flagship
- Maintenance-Eye
- Current Build
- GovtIntel RAG
- Work Context
- BCRTC asset data
Flagship Proof
Open case study →
Shipped and deployed
Maintenance-Eye
A real-time maintenance copilot that streams camera and microphone input from a phone to a FastAPI backend, orchestrates Google ADK tools, and uses Gemini Live API for native multimodal interaction.
- Tool workflows for asset lookup, knowledge retrieval, safety guidance, and work-order actions.
- Human-in-the-loop confirmation for critical actions.
- Cloud Run, Firestore, Docker, Terraform, GitHub Actions, and multi-layer tests.
Case Studies
All projects →In progress
GovtIntel
Federal procurement intelligence RAG system with ingestion, retrieval, API, prompts, and evaluation scaffolding.
Python, FastAPI, BM25, vector retrieval, pytest
Published research
ASD Prediction
Applied ML research exploring SVM and CNN approaches for ASD screening classification.
Scikit-learn, TensorFlow, Tableau