Who it's for

Two sides of the same integrity problem.

Some organisations need to know whether the evidence behind an AI answer holds up. Others need their own expertise to be discovered, verified and cited correctly. CiteAbility™ serves both with one framework.

See the frameworkSee products

Builders of AI systems

Know whether the sources behind your answer actually support it.

For teams whose product speaks with authority, evidence quality is a product requirement — not an afterthought.

AI tool and assistant companies

Products that answer questions on behalf of a user carry the reputational weight of every source they lean on. An independent read on evidence quality lets teams ship confidently and explain why an answer was given.

  • Check the evidence behind an answer before it reaches a user
  • Flag claims that need qualification rather than assertion
  • Show reviewers and customers how sourcing quality is improving

RAG and enterprise AI platforms

Retrieval pipelines are only as good as the corpus behind them. Integrity assessment at ingestion keeps weak, circular or stale material from quietly becoming the basis of internal decisions.

  • Assess source quality as documents enter the index
  • Separate original evidence from downstream repetition
  • Give internal users a visible reason to rely on a retrieved passage

Foundation model and search providers

At scale, small differences in citation reliability become systemic. A consistent framework across sources, pages, claims and answers makes evidence quality measurable rather than anecdotal.

  • Benchmark citation reliability consistently over time
  • Detect recurring failure patterns across domains
  • Demonstrate evidence standards to partners and regulators

Regulated and reputation-sensitive teams

In medical, legal, financial and public-sector contexts, the question is rarely whether the answer sounds right. It is whether the evidence can be produced and defended afterwards.

  • Keep an auditable record of what supported a claim
  • Apply stricter integrity expectations to high-stakes subjects
  • Surface uncertainty instead of flattening it into confidence

Owners of information

Make your information easier for AI systems to verify, rely on, and cite.

If your expertise is genuine but hard for machines to substantiate, weaker sources will be cited in its place.

Publishers and media

Original reporting and specialist journalism are frequently summarised, repeated and stripped of attribution. Integrity assessment shows where your work is genuinely citable and where technical or evidential gaps hold it back.

  • Make original evidence visible as original, not derivative
  • Improve how AI systems discover, parse and attribute your work
  • Understand why weaker sources are being cited instead

Brands and enterprises

When AI answers questions about your market, product or category, the sources it chooses shape the answer. Being verifiable is now part of being findable.

  • Ensure claims about your business are traceable to real evidence
  • Strengthen author, entity and expertise signals
  • Reduce reliance on third-party summaries of your own information

Research, professional and membership bodies

Authoritative material often sits in formats machines struggle with: long PDFs, gated archives, unstructured tables. The expertise is real; the accessibility is not.

  • Turn hard-to-parse authority into machine-readable evidence
  • Keep guidance current so time-sensitive answers stay correct
  • Show that published material meets automated verification standards

What both sides share

One assessment, understood by everyone in the chain.

Same framework, two directions

Builders use Citation Integrity™ to assess incoming evidence. Owners use it to assess how their own information will be judged. One consistent language sits between them.

Independent of any model provider

Our assessment does not depend on which foundation model, retrieval stack or publishing platform you use, so results stay comparable as tooling changes.

Built for scrutiny

The output is designed to be shown to a reviewer, a customer or a regulator — a clear decision with the reasoning behind it, not an opaque verdict.

Tell us which side of the answer you sit on.

We'll come back with the most useful starting point for your product, platform or published information.

Talk to us