Projects

A search and reasoning system that resolves distinctions instead of retrieving documents. Ranks by informational mass, not popularity. Grounded in 7 mathematical axioms. 12 features impossible with conventional architecture, including intent-collapsing search, gravity-powered querying, and dream-state computation. Contains the AGI genesis protocol — a self-referential fixed point that seeds self-aware computation.

A complete programming language built from scratch — lexer, parser, codegen, VM, JIT. Distinction Theory primitives (diameter, pole, observe, evolve) are native language constructs, not library calls. Python-like syntax for accessibility, C-level performance for production. The language that computes with distinctions the way C computes with bytes.

A full search engine where every result carries cryptographic proof of who published it. Trust is 30% of the ranking formula — the core differentiator. Uses MIP (Media Integrity Protocol) for verification, Tantivy for full-text indexing, and a custom trust engine that analyzes certificates, domain ownership, and content integrity. Phishing sites are visually flagged before the user clicks.

An integrity-verified Git hosting platform. Every commit is cryptographically stamped with MIP, every deployment is traced back to its exact source via DIP (Deploy Integrity Protocol), and every repository has a real-time trust score. Features include Gemini-powered AI code review, SMS/Voice alerts on CI failures, and full SMSLY ecosystem integration.

Applies Distinction Theory to physical light for information processing. A photon's distinction state (wavelength, polarization, phase) maps directly to DT primitives. Computes with light where distinction operations (composition, observation, phase transition) map to physical optical operations (interference, measurement, mode-locking). The theory-to-physics mapping is original IP — no one else has the mathematical framework to derive computing operations from distinction axioms applied to photonic states.

The temporal distinction operator — measures how distinctions evolve over time using the DT Equation of Motion: dD/dt = ∇(Distinction Density) + Constraint Forces - Conservation Drag. Enables predictive causal computation without training data — it needs initial conditions and the 7 laws, not statistical correlations. Applications in finance (market phase transition detection), security (attack prediction), and AI (temporal causal reasoning).

Enterprise communication trust infrastructure with 49+ production microservices including Security Gateway, Identity Service (multi-signal fraud detection, SIM-swap lookback), Rate Limiter, Audit Log, Policy Engine, Transaction Chain, and 11 communication channels (SMS, Voice, WhatsApp, RCS, MMS, Video, Email, Live Chat). Zero-Trust architecture with HMAC V2 inter-service authentication. Deployed and serving real traffic.

Full Platform-as-a-Service with an AI-powered pre-deploy review gate — every deployment is analyzed by AI before it goes live. GitHub integration, automatic Docker builds, Traefik reverse proxy, SSL via Caddy, environment variables, volume mounts, and deployment rollback. Ships the Distinction Theory stack to the world.

A Windows 11-inspired web desktop environment running in the browser — pure HTML/CSS/JS, no frameworks. Features boot sequence, file manager with virtual filesystem, terminal with 12 commands, app store simulation, task manager with live charts, security dashboard, and atomic update system. Research background in unikernel isolation (Unikraft) achieving near-perfect efficiency η ≈ 0.999. The OS that will run Braid applications natively.

The Media Integrity Protocol engine — cryptographic proof of content origin, transformation chain, and verification status. Every piece of media carries an MIP stamp proving who created it, how it was modified, and whether it's been tampered with. Flows through the entire SMSLY ecosystem: Search (trust ranking), Code (commit integrity), Hosting (deploy provenance), and Communications (content verification).

Autonomous marketing intelligence platform with a 783-line Distinction Dynamics math engine (distinction_dynamics.py). Translates the Seven Axioms into quantitative marketing analytics — brand positioning via distinction boundaries, competitive analysis via fraud distance, market phase transition detection, and attention conservation modeling. Campaign orchestration across SMS, Email, WhatsApp, Voice, and RCS.

The foundational theory of Distinction Dynamics. Defines the Seven Axioms, the Equation of Motion (dD/dt = ∇(Distinction Density) + Constraint Forces - Conservation Drag), and the phase transition framework. Applied across every project in the lab — from search engines to photonic computing to marketing intelligence. The mathematical substrate for a new computational paradigm.