For AI Providers
Citation Integrity™ Infrastructure for AI Systems
CiteAbility™ supports AI providers in surfacing dependable sources for their answers — an additional integrity layer that helps AI systems evaluate the evidence behind what they generate, without dictating what they cite.
By CiteAbility™ · Last updated
Key takeaways.
- Citation Integrity™ assessment can inform retrieval, RAG and answer-generation decisions.
- The API exposes checks, scores and certification verification to your systems.
- Assessments are evidence-based and explainable rather than opaque scores.
- Research partnerships are available for providers working on source evaluation.
The problem
Better AI answers require better information
Modern AI systems increasingly use:
- Search
- Retrieval
- External databases
- Knowledge systems
- Live web content
- Enterprise information
Retrieving a source does not answer a more important question: should the system rely upon it?
Citation Integrity™ is designed around that problem.
Positioning
An additional layer — not a replacement
CiteAbility™ is not seeking to replace an AI provider's:
- Ranking models
- Safety systems
- Retrieval infrastructure
- Grounding
- Verification
- Model policies
Citation Integrity™ can instead provide an additional structured input.
How it fits
The model
Step 01
Candidate information
Step 02
Citation Integrity™ assessment
Step 03
Structured integrity data
Step 04
Provider systems and policies
Step 05
Evidence selection
Step 06
AI answer
Independence
Why commercial independence matters
CiteAbility™ also works with businesses whose information may ultimately be evaluated. That creates an obvious potential conflict. We address it directly.
Commercial relationships do not determine Citation Integrity™ outcomes.
Businesses pay for
- Assessment
- Monitoring
- Analysis
- Infrastructure access
They do not buy
- Higher scores
- Certification outcomes
- Favourable benchmarks
- AI citations
- AI recommendations
A paying customer can receive an adverse assessment.
An organisation that has never purchased a CiteAbility™ product can demonstrate strong Citation Integrity™.
This principle is fundamental to CiteAbility™'s long-term role as AI infrastructure.
Where we are today
CiteAbility™ does not yet have AI-provider customers. Before offering Citation Integrity™ infrastructure to unaffiliated AI providers, we are testing and validating the framework using real-world data from AI assistants and websites owned by CiteAbility™'s founders — see our Research page for detail. No commercial relationship or payment is involved in this testing, and it does not affect the independence of Citation Integrity™ assessments performed for any customer.
Applications
Potential AI-provider applications
Citation Integrity™ may eventually support:
- Evidence assessment
- Source qualification
- Retrieval pipelines
- RAG
- AI search
- Agentic AI
- Citation workflows
- Knowledge grounding
- Enterprise AI governance
Boundaries
Provider control remains absolute
CiteAbility™ does not decide which sources a third-party AI provider must use. The provider determines:
- Whether Citation Integrity™ information is used
- How it is weighted
- When it applies
- What effect it has
- How final answers are generated
Next step
Interested in Citation Integrity™ infrastructure?
We welcome discussions with AI model providers, AI search companies, RAG platforms, enterprise AI developers and researchers.
FAQ
Frequently asked questions
The questions organisations ask us most often.
- How would an AI provider use CiteAbility™?
- As a signal of source dependability: checking whether a page's claims are clear, supported and corroborated before relying on it in an answer.
- Is there an API?
- Yes. Page checks, assessment lookups, scores and certification verification are available over the API.
- Can we collaborate on research?
- Yes. Contact us to discuss integration, evaluation work or joint research on source dependability.