NIST AI RMF
Primary concern
AI risk outcomes and lifecycle governance
EAINE operational layer
Risk tiering, AI SDLC, evaluation, operations, and evidence
Evidence
Show what supports every important claim.
EAINE connects external requirements to engineering decisions, named owners, evidence, and real-world results. It clearly separates facts from opinions, recommendations, examples, and ideas that still need testing.
Obligation-to-outcome traceA claim that others can check, question, and improve
- 01ObligationWhat must be true?
- 02ControlHow is it engineered?
- 03OwnershipWho is accountable?
- 04EvidenceWhat proves the decision?
- 05SignalWhat happens in operation?
Closed learning loopWhat happens in operation improves the control, not just the report.
External standards crosswalk
EAINE works with recognised standards. It does not replace them.
EAINE helps teams turn external expectations into engineering decisions, controls, evidence, and ongoing improvement.
ISO/IEC 42001
Primary concern
AI management system and continual improvement
EAINE operational layer
Operating model, RACI, governance controls, maturity, and learning
NIST SP 800-218A
Primary concern
Secure development for generative AI and foundation models
EAINE operational layer
Architecture, development, provenance, security validation, and release
OWASP GenAI
Primary concern
Application and agentic threat guidance
EAINE operational layer
Threat modeling, agent permissions, adversarial evaluation, and incident learning
Google SAIF
Primary concern
AI security risks and controls
EAINE operational layer
Platform guardrails, asset inventory, security, assurance, and observability
EU AI Act
Primary concern
Risk-based legal obligations and transparency
EAINE operational layer
Applicability inputs, human oversight, documentation, release, and monitoring
Compliance is context-specific. The EAINE crosswalk is an engineering orientation aid, not a claim of legal compliance, certification, or equivalence.
Evidence confidence
Not all evidence carries the same weight.
Read the meaning first. The letter is a compact reference used when claims and sources need to be traced consistently.
An authoritative requirement
A law, regulation, or recognised standard that applies to the stated context
Established guidance or research
An official framework, public guidance, or peer-reviewed research that informs the approach
Repeated real-world evidence
Comparable practitioner or operational evidence observed in more than one context
One example or illustration
A single-context observation or constructed example that helps explain or test an idea
An idea still to be tested
A proposition that should not be presented as established until reviewed evidence supports it
Worked examples
Useful examples, with their limits made clear.
The current examples are designed to explain and test the approach. Future reviews and real-world use will add stronger evidence.
Customer Support Assistant (Case 1)
A governed assistant spanning retrieval, escalation, evaluation, release evidence, and production learning across three formal exhibits.
End-to-end AI SDLC traceability · Exhibit 1 cost trade-offs · Exhibit 3 critical subset gatesRegulated Decision Support (Case 3)
Human-owned decision support with policy grounding, fairness, explanation, non-delegable judgment, and evidence lineage.
High-impact accountability and meaningful oversightMaintenance Agent (Case 2)
Bounded autonomy with tool permissions, safety limits, tool brokers, human approval, and operational auditability.
Agent control and physical consequenceThe Complete Dashboard Trap (Case 4)
Fail closed on missing provenance; twelve engineering lessons separating synthetic UI defaults from personal facts.
Provenance, output eligibility, and sensitive disclosure controlEngineering Modernization Assistant
Legacy modernization support measured by accepted outcomes, review effort, security, and maintainability.
Productivity with engineering qualityValidation progression
Build trust one level of evidence at a time.
EAINE does not present a designed example as a real case study. This path shows how an example can become reviewed, measured, and independently tested.
- 01Available now
Constructed illustration
A transparent scenario used to test completeness and usability.
- 02Review priority
Expert-reviewed example
A scenario challenged by relevant engineering, domain, and assurance specialists.
- 03Contribution path
Anonymised field observation
A permissioned account of practice, tradeoffs, incidents, or outcomes.
- 04Validation target
Measured implementation case
A bounded application with baseline, intervention, results, limitations, and learning.
- 05Long-term authority
Independent replication
Comparable evidence from multiple organisations or contexts.
Primary sources
Read the original sources.
Readers should always be able to separate EAINE's interpretation from the source itself.