AI Feature Launch Gate (Interactive)
An interactive launch-gate that walks an AI feature through the safety, governance, and readiness checks required before it ships.
Tools, frameworks, registers and playbooks for governing AI responsibly.
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Self-contained interactive tools that run right in your browser.
An interactive launch-gate that walks an AI feature through the safety, governance, and readiness checks required before it ships.
A browsable library of tooling mapped across the AI lifecycle โ data, build, evaluation, deployment, and monitoring โ so teams can see what to use at each stage.
An interactive explorer that maps AI use cases to the tooling, controls, and governance guardrails each one needs โ from selection through deployment.
Governance built for AI in anti-financial-crime programs.
A working model for quantifying the cost, benefit, and return on investment of AI initiatives across a financial-crimes program.
A practical playbook for making financial-crimes AI models explainable and auditable to regulators, model-risk teams, and internal audit.
A governance framework defining roles, controls, and review gates for AI models used across anti-financial-crime functions.
A ready-to-use workbook of model inventory, controls, and review tracking to operationalize governance for financial-crimes AI models.
A structured roadmap for scoring and sequencing financial-crimes AI use cases by value, feasibility, and risk.
Gates and checklists that decide when AI is ready to ship.
A comprehensive assurance checklist for auditing AI systems against governance, safety, and control expectations.
The playbook behind the launch gate: the criteria, roles, and decision flow for approving an AI feature to go live.
A tracking workbook to run features through the launch gate โ capturing checks, owners, decisions, and sign-off status.
Registers and models for tracking AI risk and real-world impact.
A reusable register for logging, scoring, and tracking AI risks with owners, mitigations, and residual-risk ratings.
A step-by-step guide to setting up and running the AI Risk Register: fields, scoring, ownership, and review cadence.
โฆ Supplied with AI Risk Register
A white paper on why and how to run an AI risk register, and how it fits into a broader responsible-AI program.
โฆ Supplied with AI Risk Register
A structured model for assessing the potential impact of emerging AI capabilities, with a companion write-up explaining how to apply it.
A review template for assessing organizational readiness to handle emerging AI capabilities and the risks they introduce.
A crosswalk mapping model policies to safety-review requirements, so teams can see how each policy is evidenced during review.
A register for monitoring the real-world impact of deployed AI โ capturing incidents, harms, benefits, and follow-up actions over time.
The operating layer โ councils, playbooks, and consultations.
An end-to-end AI governance playbook tailored to a financial institution's regulatory, risk, and model-governance context.
A reusable master template for building an organization's AI governance playbook โ adapt the sections to your own context.
A toolkit for running structured external-expert consultations and workshops โ planning, facilitation, and capturing findings.
A ready-to-present briefing pack for a Responsible AI Council: mandate, agenda, decision rights, and standing reporting.
Sector-specific AI strategy and use cases.
A strategy pitch for applying AI responsibly across Nigeria's oil & gas sector โ opportunities, value, and the governance to make it safe.
A catalogue of high-value AI use cases across the oil & gas value chain, with the governance considerations for each.
Study material and standards references.
A study guide covering the major AI standards and frameworks โ a reference for practitioners preparing for governance and assurance work.