Structured Epistemic Model of Truth (SEMT)

A framework for bounded truth, structural justification, and epistemic integrity

SEMT is a formal structure for epistemic modeling under constraints. It introduces verifier classes (M_n), truth layers (T_n), and a convergence horizon (𝕋) — enabling agents and systems to reason about what can be known, shown, or must remain undecided.

Rather than defining truth as fixed correspondence, SEMT frames it as epistemic accessibility — with implications for logic, mathematics, philosophy, and AI system design. The protocol is in ongoing conceptual and technical development.

For Thinkers

SEMT recontextualizes classic epistemic problems — from Gödel’s theorems to independence results like CH and P ≠ NP — as questions of layered verifiability. It offers a logic of structure, not assertion.

For Builders

SEMT informs tooling for bounded systems — including structural claim classification and epistemic filtration. Rather than verifying facts, it focuses on identifying which claims would be justifiable under a deterministic truth protocol. Current explorations include the Epistemic API (EAPI), a lightweight wrapper for evaluating LLM outputs using constrained classification types (T₀, T₁.x, ⊬, ∅).

→ Try the EAPI Demo (Early Access)

Featured Publication

📘 Volume I: Foundations, Perspectives and Shifting Paradigms
The foundational text introducing SEMT, its core logic and its paradigm-shifting implications.

→ View the Book

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For AI Labs & Researchers

If you’re exploring epistemic alignment, explainability, or structural verification for LLMs and reasoning systems, SEMT may offer a foundational lens for constraint-based output classification and protocol-based reasoning. Pilot collaborations welcome.

→ Contact for Access or Partnership