Outpace AI · Glossary
The vocabulary of AI control.
Outpace AI terms, industry concepts, and the regulatory frameworks we work to — defined for engineers, executives, and auditors.
OUTPACE AI · GLOSSARY
Outpace terms
Lastmile
Lastmile is Outpace AI's managed service that takes an AI use case from pilot to governed production in 6–8 weeks. It is methodology-led, tools-integrated, and expert-led, delivered across three phases: Qualify, Activate, and Control. The brand is always written as one word.
Lastmile overviewAI Control Plane
The AI Control Plane is the runtime layer that sits across an enterprise AI stack and gives a single place to set policy, capture audit evidence, and attribute cost. It is what makes 'governance' real at runtime rather than a stack of paper artefacts.
Control phaseQualify
Qualify is the first phase of Lastmile. Over two weeks, we scope the use case, score risk, and confirm value before any build begins. It produces a risk-tiered backlog and a go/no-go recommendation.
Qualify phaseActivate
Activate is the build phase of Lastmile. Across 6–8 weeks we deliver the use case end-to-end with governance, observability, and cost attribution wired in from day one — not bolted on later.
Activate phaseControl
Control is the ongoing operations phase of Lastmile. Outpace AI runs the policy enforcement, evidence capture, and cost attribution on a monthly cadence with a published scorecard. It is what keeps AI governed in production once the initial build is live.
Control phaseForward Deployed Engineering
Forward Deployed Engineering (FDE) is Outpace AI's embedded delivery model. Frontier AI engineers and governance architects operate inside the client environment for 6–12 months, building and operating AI systems until outcomes are real, measurable, and owned by the client team.
FDE serviceAI Readiness & Alignment
AI Readiness & Alignment is Outpace AI's preparatory service. Over 2–4 weeks we assess organisational readiness, confirm value across candidate use cases, and align executive expectations on what AI will and will not deliver in the first six months.
Readiness serviceAI Delivery & Assurance
AI Delivery & Assurance is the flagship capability line. It covers the end-to-end build of AI systems with assurance — governance, observability, evals, and cost attribution — wired in by design.
Delivery serviceAI Enablement & Capability
AI Enablement & Capability uplifts the client team to a position where they can run AI in production on their own. It covers AI engineering practice, evals discipline, on-call readiness, and the operating muscle to keep AI systems healthy.
Enablement serviceAI Security & Compliance
AI Security & Compliance covers runtime protection (prompt-injection defence, supply-chain assurance), regulatory alignment (NIST AI RMF, ISO 42001, APRA CPS 230), and the evidence chain needed to answer audit questions in days, not weeks.
Security serviceINDUSTRY · GLOSSARY
Industry terms
AI maturity
AI maturity describes an organisation's readiness to run AI at production scale across nine dimensions: Security, Governance, Observability, Data, Development, Operations, Value & ROI, Risk & Compliance, and Adoption & Change. It is measured, not asserted.
AI Maturity AssessmentAI governance
AI governance is the combination of written policy, decision rights, and runtime enforcement that keeps AI systems within agreed boundaries. Governance that exists only on paper is paperware — real governance enforces and produces evidence at runtime.
Security & ComplianceAI risk tiering
AI risk tiering scores each AI use case against criteria such as impact, reversibility, autonomy, and regulatory exposure. Higher-tier use cases attract more depth of control: more evals, tighter approvals, deeper evidence.
Qualify phaseRuntime guardrails
Runtime guardrails are policies that execute on every AI interaction — input validation, output filtering, data-access checks, escalation triggers. They are the difference between governance you can prove and governance you can only describe.
Control phaseModel drift
Model drift is the gradual degradation of an AI system's quality or behaviour over time, often without any code change. It is caused by input distribution shift, vendor model updates, or downstream data changes — and it is invisible without continuous evaluation.
Control phasePrompt injection
Prompt injection is an attack pattern where adversarial input causes an AI system to ignore its operator's instructions and follow the attacker's instead. Defending against it requires architectural choices and runtime controls — not prompt engineering.
Security & ComplianceAI evidence chain
The AI evidence chain is the runtime record — traces, decisions, approvals, data accesses, costs — that proves an AI system behaved within policy when it mattered. It is what makes audit responses days rather than weeks.
For the CRO / CISOAI Council
An AI Council is the cross-functional body — typically including CIO, CISO, CRO, legal, and a business owner — that owns AI policy, risk tiering, and exception approvals. It is where the difficult judgement calls happen and where accountability lives.
Lastmile operating modelAI portfolio
An AI portfolio is the full set of AI use cases an organisation is running, scoping, or scaling. Managed as a portfolio — not as one-off projects — it gets prioritised against capacity, risk appetite, and outcome value.
Readiness serviceREGULATORY · GLOSSARY
Regulatory terms
NIST AI RMF
NIST AI RMF is the AI Risk Management Framework published by the US National Institute of Standards and Technology. It is the most widely-adopted control reference in enterprise AI and is the basis for many other frameworks (including parts of ISO 42001).
Security & ComplianceISO 42001
ISO 42001 is the international management-system standard for AI, modelled on ISO 27001 for information security. It defines what an AI Management System looks like and what evidence an organisation must produce to be certifiable.
Security & ComplianceAPRA CPS 230
CPS 230 is the Australian Prudential Regulation Authority's operational risk management standard for banks, insurers, and superannuation entities. It applies directly to AI systems used in regulated processes — particularly the requirements around critical operations, third-party service providers, and business continuity.
Financial servicesAUSTRAC AI guidance
AUSTRAC has issued guidance on the use of AI in anti-money-laundering and counter-terrorism-financing programs, including expectations on model explainability, oversight, and the boundary between AI-assisted and AI-automated decisions.
Financial servicesEU AI Act
The EU AI Act is the European Union's regulation classifying AI systems by risk tier (unacceptable, high, limited, minimal) with corresponding obligations. It applies to any organisation putting AI systems on the EU market, including Australian providers serving EU customers.
Security & ComplianceReady when you are
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