ai-praxis-tool
Synthetic banking AI risk management control tower demonstrating AI inventory, risk assessment, mitigation planning, controls, evidence tracking, ownership, and framework mapping.
Identity verification for AI-governed systems: passwords, authenticator codes, phone codes, voice and biometric match, knowledge-graph questions, and the assurance level each action needs.
The umbrella that assembles the Vega SDK family as one organism: registry, one keyed ledger, one approval check, pre-deploy audit.
Gated command execution for people and AI agents: nothing runs without an approved commitment.
Licence-aware knowledge graph with provenance for every fact and a predictive lattice.
Proof of need and proof of payment: a co-signed constitution, advisory need analysis, human-approved releases from a simulated bankroll, institution receipts and privacy-preserving proof of income.
The galaxy view of a knowledge lattice: necessary conditions from below, possible futures from above.
AI Control Engineering baseline package converting a synthetic enterprise AI assistant into system inventory, risks, controls, evidence, tests, and executive findings.
Governed model training that records exactly what a model learned from, with held-out test separation.
Adapter and quarantine layer: admits only what the owner announced and holds unknown agents in a dead-end room.
Anonymous multi-brain deliberation that always carries dissent, plus a design-first builder with human taste decisions.
Jurisdictional protocol keys for AI governance: branch keys, a 2-of-3 policy, a public veto and the hard-stop root, so legal minimums are enforced in code.
Governance hardware reference model in software: a Governance Enforcement Unit and a runtime unit that enforce human-signed, single-use commitments, with power-cut safe memory and a hard stop.
Live view of every governance chain with tamper alarms.
Evidence rungs and a completion gate: an AI cannot claim done without the evidence.
Human-only authority for AI agents: single-use, time-limited signed commitments with entry and exit gates.
Lessons and memory of past incidents so an AI system learns from what went wrong.
Telemetry of AI reasoning: layer traces, entropy, harmonic echo and a reference signature.
Layered sealing and proof tiers for private data: zero-knowledge interfaces, updatable encryption, fail-closed tiers.
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