I build ambient AI systems, presence infrastructure, and developer tools that operate at the boundary where technology becomes invisible: running on your hardware, under your control.
Tests are contracts. Thousands of them run across the portfolio, on every build.
On the bench now: an always-on local assistant, autonomous agents running on my own hardware, and local document comprehension. Details when the filings clear.
Every project under the Liminal umbrella shares one conviction: the most powerful technology is the kind that disappears into your environment. Local inference. Privacy by architecture. Zero cloud dependency.
An always-on AI that runs entirely on consumer hardware. All behavioral intelligence lives in deterministic code rather than prompt engineering, so the model underneath is a commodity and the system around it is the product. Patent-pending orchestration.
Algorithmic trading engine built on a J-pattern detection system with an 8-state finite state machine. Runs live and fully audited: every fired signal is logged and resolved through the cascade, and the whole session reconstructs from the decision ledger.
Receipt capture and categorization. Pulls line items, vendors, and totals from photos and PDFs, backed by a 4.3-million-product barcode catalog, and feeds structured data into personal and business accounting.
A fully local wine cellar tracker. Every bottle runs a lifecycle from ordered to poured, grounded by a 100,646-wine reference database with on-device label reading. Your cellar, your data, your network.
Local video-comprehension pipeline. Transcribes audio, deduplicates frames, and recovers on-screen text the narration never says: 85% of frames pruned, 1,295 lines recovered from a single source. CPU-only, no cloud.
A shopping list that thinks. It auto-categorizes items and orders them by a per-store walk path, so the list lines up with the aisles. Self-hosted, mobile and desktop.
Real-time status synchronization across platforms with a pure-mirror architecture: any status change propagates everywhere, with no precedence logic and no hierarchy. Multi-calendar sync across M365 and Google. Currently being rebuilt.
CLI tool for training and deploying custom wake words. CPU-only inference, Docker-first, ONNX output. Built for edge devices that need always-on voice without a cloud round-trip.
Android auditor for battery drain, permission creep, and deadweight apps. It surfaces what is quietly costing you, and why.
Structured multi-agent deliberation. Independent AI instances work through a shared workspace, one driving execution and one driving critical analysis, across dedicated build and deliberate modes.
End-to-end synthesized presenter video. Voice synthesis paired with visual generation produces natural conversational avatars from a single reference image and voice sample. Built for personal content production; all training data self-sourced and consented.
I believe the next generation of intelligent systems won't live in distant data centers. They'll run on your hardware, in your space, under your control. Every tool I build prioritizes local inference, privacy by architecture, and the principle that the best technology is the kind you stop noticing.
My engineering philosophy is simple: all behavioral intelligence lives in deterministic code. Models are commodities, replaceable and benchmarked and never the moat, and the system around them is the product. That makes what I build vendor-proof, auditable, and able to outlast any single model generation.
If it can run on your hardware, it should. Cloud is a fallback, not a foundation.
Swap the model, keep the system. The architecture survives any vendor decision.
Intelligence in code, not prompts. Testable, auditable, reproducible behavior.
Your data never leaves your network. No telemetry, no training, no exceptions.
Liminal Technologies Group is my IP holding company and development lab. I build at the intersection of AI infrastructure, enterprise operations, and edge computing.
The same discipline that standardizes software across complex organizations is the discipline that builds AI systems engineered to outlast any single model generation. I bring an operator's mindset to every project: ship it, instrument it, make it survive contact with the real world.
My background spans enterprise ERP implementations, automation at scale, decades of hands-on industrial and fabrication work, and AI systems integration. The kind of engineering that only comes from solving real problems in production, not in a lab.
Local AI infrastructure, enterprise rollouts, and automation built to survive vendor churn. Inquiries, partnerships, and interesting problems welcome.
Or reach me directly at [email protected]