Sifaka is an open-source framework that adds reflection and reliability to large language model (LLM) applications.

This project integrates Hyperledger Fabric with machine learning to enhance transparency and trust in data-driven workflows. It outlines a blockchain-based strategy for data traceability, model auditability, and secure ML deployment across consortium networks.

A long-form article and practical framework for designing machine learning systems that warn instead of decide. Covers regimes vs decimals, levers over labels, reversible alerts, anti-coercion UI patterns, auditability, and the “Warning Card” template, so ML preserves human agency while staying useful under uncertainty.

A framework that makes AI research transparent, traceable, and independently verifiable.

Governance beneath the model. Custody before trust. Open for audit. Constitutional Grammar for Multi-Model AI Federations, Firmware Specification • Zero-Touch Alignment • Public Release v1.0

An ethics-first, transparent AI reasoning assistant. Built to be self-hosted by anyone.

Proof of Human Intent (PoHI) - Cryptographically verifiable human approval for AI-driven development

BLUX-cA — Clarity Agent core of the BLUX ecosystem. A constitutional, audit-driven AI helm that interprets intent, enforces governance, and routes tasks safely across models, tools, and agents.

A principal-level framework for governing AI-assisted decisions with accountability, auditability, and risk controls.

Self-auditing governance framework that turns contradictions into verifiable, adaptive intelligence.

Digital Native Institutions and the National Service Unit: a formal, falsifiable architecture for protocol-governed institutional facts and next-generation public administration.

Governance, architecture, and epistemic framework for the Aurora Workflow Orchestration ecosystem (AWO, CRI-CORE, and scientific case studies).

Not new AI, but accountable and auditable AI

Winmem keeps Solana projects alive without maintainers.

omphalOS turns strategic trade-and-technology analyses into tamper-evident, "run packets" for inspector, counsel, and oversight review.

Reference implementation of the Spiral–HDAG–Coupling architecture. It combines a verifiable ledger, a tensor-based Hyperdimensional DAG, and Time Information Crystals to provide a new kind of memory layer for Machine Learning. With integrated Zero-Knowledge ML, the system enables trustworthy, auditable, and privacy-preserving AI pipelines.

An OSS, developer-focused Consent Management Platform sample which includes functionality for granular data types, proxy consent, age-specific flows, revocation/updates, auditability, extensibility. Demo site included below.

完全ローカル×思考可視化×三権分立の軽量AIコア。ネット/外部DBなし。state保存/復元、4D意味距離(geo/strict)、署名付き役割カード、𝒢実装。

Agentic RFP response system orchestrating Sales, Technical, and Pricing agents with human-in-the-loop governance for fast, auditable enterprise responses.

A governed system for translating applied AI research into auditable, decision-ready artifacts.