A

auditability

OpenLedger Provenance System is an append-only, event-sourced knowledge infrastructure that records how information evolves over time through verifiable chains of events, evidence, and methods. It is designed for high-trust environments such as scientific research, archaeology, legal systems, and civic data, where every claim must be traceable, reproducible, and transparently linked to its origin and reasoning. https://roxanneardary.com/openledger-provenance-system/

AuthorityCore is an open-source AGPL 3.0+ focus-oriented AI governance and reliability framework designed to improve long-horizon task execution by reducing possibility space, enforcing objective contracts, and ensuring jurisdiction-aware, evidence-based, and fully traceable workflows under continuous human oversight. https://roxanneardary.com/authoritycore/

TraceCommons is an open-source transparency and provenance infrastructure that uses Merkle-based append-only logs, witness verification, and cryptographic timestamp anchoring to create independently verifiable digital records. It extends into AI provenance tracking, enabling datasets, models, and generated content to be traced and audited across their full lifecycle, helping establish trustworthy digital history in the AI era. https://roxanneardary.com/tracecommons/

Securekit is a protocol-agnostic security kernel that enforces zero-trust, sandboxed execution for AI tool use. It sits between any LLM or agent system and its tools, validating, isolating, and auditing every action to prevent unsafe execution across MCP, OpenAI tools, and custom AI protocols. https://roxanneardary.com/securekit/

SecurePath is an open-source, enterprise-grade framework for AI evaluation, red-teaming, and regulatory compliance. It provides sandboxed testing, policy-aligned metrics, multi-modal evaluation, training data sensitivity analysis, and historical compliance tracking, all while maintaining audit-ready logs and dashboards. Designed for organizations, enterprises, and research teams, SecurePath ensures AI safety, transparency, and regulatory assurance. https://roxanneardary.com/securepath/

Crystal Ledger is an open-source custodial financial infrastructure platform built to replace opaque banking systems with verifiable, transparent, and cryptographically auditable accounting. Designed around sound money principles and Bitcoin-first treasury management, it provides real-time proof of reserves, immutable financial records, and deterministic interest accounting. Every balance, liability, and yield source is structured to be independently verifiable, ensuring that financial trust is replaced by mathematical proof. https://roxanneardary.com/crystal-ledger/

The Interpretation Layer is a modular, human-in-the-loop AI system that transforms structured moral interpretations of textual passages into modern, grounded human narratives. It uses a transparent pipeline where AI suggests ethical meanings, humans validate the intended moral, and the system generates narrative outputs based on that selection. Designed for auditability and neutrality, it functions as a computational layer between text and meaning rather than an authority on interpretation. https://roxanneardary.com/the-interpretation-layer/

Human Decision Specification (HDS) is an open, modular standard for building AI systems that keep humans in control of decision-making. It defines a structured workflow where AI systems ask clarifying questions, discover and confirm human intent, evaluate legal and compliance constraints, and provide transparent recommendations. HDS ensures that every significant action is approved by a human, fully auditable, and designed to prevent autonomous decision-making without oversight. https://roxanneardary.com/human-decision-specification/

BreakSignal is an open-source AI audit framework that evaluates consistency, transparency, and factual reliability across AI systems by running structured prompt tests, comparing outputs, and measuring inconsistency at scale. https://roxanneardary.com/breaksignal/

Human Intent Governance Standard (HIGS) is a structured framework for building AI systems that operate under verified human intent, enforceable policy, and auditable compliance. It ensures that every decision passes through intent clarification, legal and policy validation, risk assessment, and human approval before execution. Designed for regulated and high-trust environments, HIGS prioritizes transparency, explainability, and human accountability while enabling modular, extensible governance across legal, technical, and organizational domains. https://roxanneardary.com/human-intent-governance-standard/

Odessa Drive is an open-source, AI-powered vehicle intelligence system that uses voice input and GPS tracking to automatically log business mileage, fuel purchases, and vehicle repairs. It maintains structured, audit-ready records and applies versioned IRS tax rules to support compliant, transparent reporting and decision-making. https://roxanneardary.com/odessadrive/

ResponseOS is an open-source platform for reproducible clinical research analysis that re-examines medical studies to identify what truly drives patient outcomes. It aggregates and normalizes clinical trial data, applies Bayesian and meta-analytic methods to measure treatment effects against placebo signals, and highlights areas requiring further biological investigation. Designed for transparency and auditability, ResponseOS builds a continuously updated knowledge system where all analyses are versioned, reproducible, and open to scientific scrutiny under the AGPL-3.0+ license. https://roxanneardary.com/responseos/

CortexLoop is a human-in-the-loop AI orchestration system designed to keep all reasoning, planning, and execution fully transparent, structured, and under human control. It transforms AI from an autonomous or opaque assistant into a governed cognitive loop where multiple solution paths are generated, evaluated for risk and confidence, and returned to the user for decision-making. Every action is logged through a decision ledger, enforced by a policy engine, and constrained by strict system rules including AGPL+ licensing and attribution requirements. The result is a traceable, auditable AI system that prioritizes clarity, accountability, and human authority at every step. https://roxanneardary.com/cortexloop/

Atlas Urban Intelligence is an AGPL 3.0+ modular smart city AI system that transforms distributed edge sensor data into real-time, event-based urban intelligence. It is designed around privacy-by-default principles, ensuring no persistent identity tracking while enabling scalable analysis of real-world motion across intersections, highways, and urban environments. The system combines edge inference, federated learning, and a policy-driven compliance layer to deliver transparent, auditable, and privacy-preserving city-scale intelligence. https://roxanneardary.com/atlas-urban-intelligence/

Vexa is a privacy-first, human-in-the-loop AI orchestration platform that connects and automates enterprise tools through a secure, auditable control layer. It enables users to build and execute multi-step workflows across systems like Slack, Jira, and Salesforce while enforcing strict privacy controls, zero-trust data handling, and full execution transparency through explainable, replayable actions. https://roxanneardary.com/vexa/

Chainly is an open-source AI-powered data flow intelligence system that traces what happens to user data after login events across the web. It builds evidence-based graphs of how information moves between first-party services, third-party vendors, and data brokers, revealing real-world data sharing that is often hidden behind privacy policies. By combining network tracing, graph analysis, and AI-driven entity resolution, Chainly turns invisible post-login data propagation into a transparent, auditable system. https://roxanneardary.com/chainly/

PhysicsMesh Platform is a law-driven simulation system that computes physical reality through invariant physics laws rather than approximation or animation heuristics. It combines modular physics engines, spatiotemporal computation, versioned material science, and full source-method-provenance tracking to ensure every simulated outcome is causally consistent, reproducible, and scientifically traceable. Rendering is strictly a downstream projection of solved physical states in 2D or 3D space, governed by a human-in-the-loop intent and consent system that ensures all simulations are explicitly authorized and auditable. https://roxanneardary.com/physicsmesh-platform/

The Foundation for Deterministic Computing (FDC) is an open standards initiative dedicated to building reproducible, auditable, and human-governed computing systems. It defines modular specifications for deterministic execution, verifiable intelligence, structured knowledge, and transparent decision-making. The foundation provides a framework for ensuring that computational systems operate with consistency, traceability, and accountability across all layers of software and intelligent infrastructure. https://roxanneardary.com/foundation-for-deterministic-computing/

CommonsProtocol is an open-source civic transparency platform that provides a public, auditable infrastructure for political campaigns, governments, and civic organizations. It enables real-time visibility into donations, spending, and governance finances through a federated, append-only ledger system designed for accountability, trust, and public oversight. https://roxanneardary.com/commonsprotocol/

AuthTrace AI is an AGPL-3.0+ licensed provenance and licensing intelligence system that verifies authorship, tracks content lineage, and transforms human-created knowledge into structured, licensable digital assets. It provides a trust and economic layer for the open knowledge ecosystem, enabling transparent attribution, distribution, and monetization while preserving creator ownership and enforcing attribution integrity across all derived works. https://roxanneardary.com/authtrace-ai/