Projects

AI projects and case studies built around real workflows.

These examples show how practical AI systems can support workflow selection, client intake, grounded answers, review loops, and production-ready operations.

Selected work

Review live tools and case studies.

Each project is designed to show how AI can fit into a concrete business process with a clear user, workflow, and operating outcome.

Workflow assessment

Founders, COOs, CTOs, and operators

AI Workflow Readiness Scorecard

Teams know AI matters but cannot rank which workflows are worth building first.

Buyer Problem Solution Evidence

Buyer: Founders, COOs, CTOs, and operators
Business problem: Teams know AI matters but cannot rank which workflows are worth building first.
Solution pattern: Interactive diagnostic that scores workflow fit, data readiness, risk, guardrails, and ROI potential.
Stack: Python, deterministic scoring engine, OpenAI recommendations, Supabase persistence, Cloud Run
Evidence: Live assessment app with explainable scores, deterministic fallback, tailored recommendations, and protected submissions.

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Live case study

Business owners, office managers, brokers, practice managers, front desk leads, and service teams.

Frontline AI Business Assistant

A client-facing assistant that helps service businesses answer routine questions, capture requests, book appointments, and keep staff focused on higher-value work.

Buyer Problem Solution Evidence

Buyer: Business owners, office managers, brokers, practice managers, front desk leads, and service teams.
Business problem: Many teams lose time and opportunities because calls, messages, bookings, follow-ups, and policy questions are handled manually across too many places.
Solution pattern: A guided assistant that gives approved answers, collects the right details, creates follow-up items, and gives the team a clear view of client conversations and requests.
Stack: React, FastAPI, tenant-aware database layer, OpenAI Agents SDK, knowledge search, Netlify
Evidence: Reviewable demo with multiple office types, public demo access, client chat, appointment capture, request review, business activity dashboard, and readiness assessment handoff.
Outcome: Faster replies, cleaner intake, fewer missed inquiries, better follow-up, and less repetitive admin work.

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Why this matters

These are examples of AI systems built around real operating problems, not demos looking for a use case.

Each project shows how I turn messy workflows into practical tools that help teams respond faster, capture better information, keep staff in control, and make the next operational step visible.

Pick the right workflow first

Answer routine questions faster

Capture cleaner client intake

Give staff a review surface

Reduce repetitive admin work

Track activity and follow-up

Launch with guardrails

Improve from real usage