Social Anger Labs
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SAL—01
Social Anger Labs is an applied AI R&D organization building practical systems for high-stakes domains where friction, accountability, and precision matter most — education compliance, knowledge economies, and institutional governance. We treat disagreement, dissent, and rigorous scrutiny as essential signals, not noise.
We focus on the legal, financial, and educational workflows most AI labs avoid — accreditation cycles, verifiable knowledge assets, adversarial mediation, governance infrastructure. Where the system actually has to work.
Friction, accountability, and precision are not bugs to be smoothed out. They're the conditions under which serious institutions operate, and the parts of public life that most AI tools are built to avoid.
We design for the opposite — disagreement-tolerant agents, auditable knowledge assets, decision standards you can argue with on the merits. Tools for teams and systems that have to defend their work.
Our stack is load-tested in real institutional environments and designed for trust, auditability, and measurable outcomes. We work in public when we can, in private when we have to.
A protocol for AI knowledge as verifiable, tradable assets. Publish, license, and monetize prompts, skills, projects, and distilled intelligences on-chain. Agents execute real Offers with governed tools, full provenance, and royalty enforcement.
A decision-standards engine and living workspace for accreditation and compliance. Powered by Stan — your institution-specific AI agent that ingests self-studies, exhibits, policies, and evidence, then supports drafting, gap analysis, and audit readiness with grounded citations.
A secure administrative operating system designed to stabilize identity, map jurisdiction, and reconcile obligations across institutional domains with precision. GIMS treats courts, financial systems, administrative agencies, and tax authorities not as separate silos, but as surfaces of the same underlying execution logic.
Mapping how dissent, scrutiny, and institutional friction propagate — using topologies, not shallow sentiment. Applied to compliance monitoring, public discourse analysis, and decision environments.
Systems that sit between conflicting requirements, stakeholders, or data sources without flattening the differences. Conflict-tolerant agents and protocols for legal, financial, and educational contexts.
Quantitative and linguistic measures of how trust erodes in institutions and documents. Early signals in language, evidence quality, and compliance health — before they show up in outcomes.
Simulating stakeholder responses, policy impacts, and system loads — then testing real tools against them. A wind tunnel for standards, products, and governance frameworks.
We collaborate with researchers, operators, institutions, and builders working on complex governance, compliance, knowledge markets, or conflict-aware AI. Tell us what you're trying to do — we'll route you to the right line.