Independent by design
We are not tied to any foundation model, retrieval stack or publishing platform, so an assessment stays comparable as the underlying technology changes.
Why we exist
Integrity should be infrastructure, not an afterthought.
AI answers now sit between people and the information they rely on. That makes the quality of the evidence behind an answer a shared responsibility.
The failures we see are consistent: citations that go nowhere, sources that don't support the claim, repetition mistaken for corroboration, and authoritative material that machines simply cannot read. None of these are solved by better wording.
CiteAbility™ exists to make those failures visible and measurable, using one framework that works for the teams building AI systems and for the organisations whose information those systems depend on.
How we work
Three commitments that shape everything we assess.
Evidence before opinion
Every judgement traces back to something checkable: a source, a claim, an attribution, a date. If it cannot be evidenced, it is not asserted.
Precise about the claim
We describe exactly what our work improves — measurable citation and evidence quality — and we are equally clear about what it does not promise.
The founders
Built by people who have spent careers on dependability and technology.
CiteAbility™ was founded by Chris Emmins and Mark Barclay, combining information-integrity practice with hands-on AI systems delivery.
Chris Emmins
Co-founder
Founder and CEO of KwikChex, with a background in information integrity, verification, consumer protection and fraud prevention.
Two decades of work on how claims are substantiated, challenged and corrected at scale informs how CiteAbility™ assesses evidence.
Mark Barclay
Co-founder
Founder of SynaBot, with a background in AI assistants, LLM applications and commercial AI implementation.
Hands-on delivery of production AI systems shapes how CiteAbility™ fits into real retrieval, generation and review workflows.
Responsible claims
We are precise about what this does.
Citation Integrity™ is designed to reduce measurable integrity failures in AI-sourced evidence. We don't claim to eliminate AI hallucinations or guarantee that cited content is true — we validate specific, measurable improvements in citation and evidence quality.
Talk to CiteAbility™ about your AI integrity needs.
Tell us what you're building or publishing, and we'll come back with the most useful starting point.