Building the infrastructure layer between language models and the domains where their mistakes carry real consequences — legal practice, healthcare, professional accountability.
A sequence of papers developing a geometric and field-theoretic framework for AI memory architecture — from discrete graph theory through scalar-tensor gravity on hyperbolic belief manifolds.
Introduces a discrete geometric framework for knowledge graphs in which beliefs carry a local metric tensor, contradictions manifest as negative Ollivier–Ricci curvature, and information homeostasis emerges from the balance of a curvature-smoothing flow and epistatic regulation.
Instantiates the RBM framework in the Poincaré disk with zone-specific inertia values encoding epistemic authority. Develops the HSH metric, the curvature-adaptive signed Laplacian, and the coherence field as a memory commit criterion.
Presents VeritasMemoria's three-layer defense architecture: immutable Task Registry, three-gate memory validation with hyperbolic quarantine, and a five-domain goal stability invariant. Empirical evaluation across 3000+ simulated attacks demonstrates 98–100% detection for overt attacks and zero successful hijacking.
Derives a closed-form scalar-tensor field theory from the HSH architecture. Proves via the Bianchi identity that contradiction stress is conserved and can only be removed by human intervention — a field-theoretic derivation of the system's architectural human-oversight requirement.
Production systems built to solve specific problems in high-stakes domains.
Local-first AI memory architecture for legal practices, healthcare providers, and independent professionals. Four-zone belief graph with cryptographic audit trails, human-gated contradiction resolution, and the geometric validation layer developed in the research program.
Lead intelligence pipeline with waterfall-style source prioritization — cheapest/fastest sources first, escalating to richer sources only when needed. Includes idempotency layer, rate limiter, execution engine with producer/worker separation, and doubt-scored signal quality assessment.
Code that exists to be useful, not to be impressive.
Waterfall lead intelligence pipeline with idempotency, rate limiting, and doubt-scored signal quality.
Simulation code for gradient flow dynamics on hyperbolic belief graphs. Verifies the scalar-tensor field theory empirically.
Base-26 opaque timestamp encoder producing human-unreadable but deterministically decodable sigils for audit trail entries.