Work and demos, with honest availability labels.
This page reframes the demos as evidence for employers and technical decision-makers. Each example shows what it proves, where the safety boundary sits, and whether the work is public, protected, prototype, or internal-only.
Production / public
Public surfaces that can be reviewed directly, with claims limited to what is actually available.
Protected demo
Interactive surfaces behind access control, email allow-listing, and manual approval where risk requires it.
Prototype / internal-only
Architecture, workflow, and outcomes are public; private systems, credentials, customer data, and internal infrastructure stay private.
Proof hierarchy
The point is credibility, not demo volume.
Clinical AI is the strongest employer signal. Operations and MRO show workflow translation. Trading, security, and music add range, data scale, boundary-setting, and product proof.
Every card states what the work proves, not just what it is.
Status labels distinguish production, protected demo, prototype, and internal-only work.
Sensitive domains use synthetic data, access controls, and conservative public boundaries.
Work examples
What each system proves.
The cards are written for evaluation: value proposition, employer proof, and safety or access boundary.
DRG Clinical Validation
Coder-grade DRG validation built around an extraction -> normalization -> validation -> human-review loop with explicit guardrails.
Unstructured clinical inputs become structured, auditable outputs with a human-in-the-loop gate before anything moves downstream.
Live demo behind Cloudflare Access. Email allow-list, no patient data. Manually reviewed within 24 hours.
TwoSevens Music
AI-assisted artist catalog and karaoke-style listening demo, with stem-extraction studio tooling kept internal until it is ready to be public.
End-to-end music surface: hosted catalog, public listen demo with karaoke-style lyrics, and a credible bridge from catalog into SongCraft commerce.
Public catalog and listen demo are live. Stem extraction is internal studio tooling. No public commerce, payouts, or admin panels are exposed.
SongCraft
Personalized-song commerce MVP - order intake, Stripe checkout, AI-assisted generation, human review, and MP3/lyrics delivery for the occasions that deserve a track.
Generative-AI commerce loop built end to end with explicit review gates between request, payment, fulfillment, and delivery - not a one-click black box.
MVP is code-complete and merged, running manual fulfillment in Stripe test-mode staging only. No public checkout and no live payments - production launch stays gated until the launch-readiness criteria are signed off.
RegenITAD - MRO Asset Listing
AI-assisted listing pipeline for ITAD and surplus IT equipment: extraction, vendor enrichment, normalization, and review before any draft is exported.
Workflow-gated state with evidence capture and compliance-aware document generation. AI accelerates, humans approve.
Planned MVP. Sample / synthetic assets only - no real customer asset tags, no direct marketplace publishing in MVP.
Opportunity Evaluation
AI-assisted opportunity evaluation and validation: extract requirements, validate fit, identify gaps and risks, score evidence, and prepare reviewer-ready next steps.
The same criteria-driven workflow can evaluate jobs, RFPs, vendors, partnerships, sales leads, and other opportunities without becoming an auto-apply bot.
Public proof uses synthetic/sample opportunity data only. No real resumes, recruiter emails, job applications, private documents, or personal data are shown.
Security Platform
Controlled white-hat research sandbox with real-time monitoring, anomaly detection, and compliance reporting.
Defensive posture and reporting hygiene - alerting paths, evidence trails, and reviewer workflows wired up before any tooling.
Authorized use only. Lab/synthetic targets only. No live offensive tooling, internal targets, credentials/secrets, or public scanner access.
Trading / ML Platform
Simulation-only ML research surface for historical market data, feature engineering, model workflow experimentation, backtesting, and risk-control review.
Production ML lifecycle discipline: historical/synthetic data ingest, feature store, experiment tracking, replayable backtests, and explicit risk controls.
Historical/synthetic analysis only. No financial advice, live broker execution, credentials, account balances, or order routing are exposed.
Infrastructure Lab
Distributed operations across ~25 servers with operator-controlled orchestration, monitoring, and recovery discipline.
Multi-node operation is treated as a real product surface - service separation, queue-backed work, and recoverability are first-class.
Architecture and outcomes only. No internal hostnames, IP ranges, admin URLs, or credentials are published.
DRG Clinical Validation
Coder-grade DRG validation built around extraction, normalization, validation, and human review. The live interaction is gated behind Cloudflare Access, uses synthetic / non-PHI examples, and is manually reviewed before access is granted.
Need a focused evaluation path?
Start with the work examples, then open a hiring or workflow conversation. Protected demos stay gated; public pages keep claims conservative.