BBBD’s AI Validation Framework ensures all knowledge used by AI, automation and digital workers is accurate, consistent and standards-aligned before it reaches your customers or staff.
Why AI validation matters
AI is only as good as the knowledge and structure it relies on.
Unvalidated AI can misinterpret policy, apply outdated rules, hallucinate facts or give different answers to the same question across channels. In Government and regulated sectors, this introduces operational, legal and reputational risk.
BBBD’s AI Validation Services make sure your AI and digital workers always draw on a single, validated version of the truth — expressed in a way that both humans and AI can use safely.
What AI validation ensures
Validated knowledge becomes a safe foundation for automation and AI.
In BBBD’s framework, validated knowledge is:
- structurally correct
- consistent across channels
- up to date
- free from duplication
- mapped to the correct audiences
- compliant with accessibility and content standards
This means AI is always using the right rules, expressed the right way, for the right people.
Our AI Validation Services
Six core validation services that together make AI safe, structured and reliable.
1. Structural Validation
Structural Validation checks that your content is organised in a way that both humans and AI can reliably interpret.
We check for issues such as:
- missing or incorrect headings and hierarchy
- multiple H1 headings or broken anchor points
- sections that are in the wrong order or scope
- content that doesn’t follow agreed patterns or templates
The result is a clean, well-structured knowledge base that AI can navigate without confusion.
2. Consistency Validation
Consistency Validation identifies where your current content sends mixed messages or contradicts itself across documents, channels or teams.
We identify:
- conflicting statements and contradictory rules
- overlapping or competing content covering the same topic
- outdated versions that conflict with current policy
- policy mismatches between related documents or processes
This ensures AI doesn’t have to “choose” between multiple answers, and staff aren’t arguing with different versions of the truth.
3. Accuracy Validation
Accuracy Validation ensures that the content AI relies on is factually correct and aligned with current legislation, policy and operational rules.
We ensure:
- legislation references are correct and current
- parameters and thresholds match approved policy
- entitlements and conditions are clearly and correctly expressed
- logic and decision paths are unambiguous
This reduces the risk of AI giving incorrect advice, misquoting policy or misrepresenting entitlements.
4. Duplicate Detection
Duplicate Detection removes unnecessary repetition and overlapping content that can confuse both people and AI.
We remove or rationalise:
- non-boilerplate duplicates across documents and channels
- near-duplicate paragraphs that differ only in wording
- duplicate rules expressed in slightly different ways
- redundant variations that cause inconsistent AI behaviour
After this step, AI sees a coherent, clean set of rules — not five subtly different versions.
5. Standards Compliance
Standards Compliance ensures your content is aligned with accessibility and content standards recognised across Government and the public sector.
We align with standards such as:
- NZ-WAS 1.2 and NZ-WUS 1.4
- WCAG 2.2 AA accessibility guidelines
- UK-GDS content patterns and plain language principles
- other sector or agency-specific standards as required
This improves accessibility for people, and also gives AI better-structured content to work with.
6. AI Readiness Validation
AI Readiness Validation tests whether your validated content can actually be used reliably by AI models in real-world scenarios.
We test:
- whether AI can parse the content and structure correctly
- whether the structure is genuinely machine-readable
- whether variables, conditions and examples are clear to AI
- whether AI is likely to misinterpret key terms or rules
This step confirms that content is not just correct on paper, but usable and safe when AI is in the loop.
Outcome of AI Validation
A knowledge base that AI — and your people — can trust.
A validated knowledge base ensures that AI always uses:
- the correct version of the truth
- the correct structure
- the correct rules
This eliminates misinformation, reduces organisational risk and creates a stable foundation for Responsible AI and governed automation.
Validated AI inside a governed ecosystem
Validation is tightly integrated with Responsible AI and WorkHub 360.
AI Validation Services are part of the broader BBBD ecosystem:
Responsible AI sets the guardrails and decision boundaries, while WorkHub 360 governs digital worker identities, logs and metrics.
- validated knowledge becomes the single source of truth for AI
- AI behaviour is logged, monitored and explainable
- confidence thresholds and escalation paths are enforced
- digital workers and AI models operate within clear boundaries
- evidence is always available for audit, risk and governance teams
What CXOs gain from AI Validation Services
Confidence to deploy AI where it matters most.
- reduced risk of incorrect or inconsistent AI advice
- faster sign-off from risk, legal and governance functions
- better customer and staff experiences with AI-assisted channels
- a clear, evidence-based story for Boards and Ministers
- confidence to expand AI into more processes and channels
- a repeatable pattern for validating future AI initiatives
Ready to validate your AI?
Let’s take a real policy, process or service area and run it through the AI Validation Framework — so you can see exactly how structural, consistency, accuracy, duplicate, standards and AI readiness checks make AI safer and more reliable
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