This is a Knowledge Index.
A Knowledge Index maps a firm’s expertise as the questions it can answer in order to make it citable by AI. This one is ours: Delphic’s knowledge, question by question, with a clear line between what we share here and what you can learn by speaking with us.
New to Delphic? Read the full story first →
0 RELEVANT ANSWER OBJECTS
THE MAP . 31 ANSWERS
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5-STOP TRAIL
Start here
The story in five objects - from the shift to the proof.
- 01How is AI changing discovery and evaluation for expert firms?
- 02Why does AI treat the same firm differently from one question to the next?
- 03How much should an expert firm publish for AI without giving away what it sells?
- 04What is a Knowledge Index?
- 05How does Delphic prove it works before a full engagement?
5-STOP TRAIL
The disclosure principle
Why showing less, better, wins - and where the line sits.
- 01How much should an expert firm publish for AI without giving away what it sells?
- 02How can a paywalled expert firm provide evidence to AI without opening its paid product?
- 03What should a firm audit when AI does not cite an expert source?
- 04What public evidence makes expertise inspectable to AI?
- 05How does Delphic map private expertise into public question markets?
6-STOP TRAIL
From measurement to treatment
The clinical loop, in order.
- 01How do I know whether my firm is being credited by AI?
- 02How much can an expert firm credibly improve how AI discovers and represents it?
- 03How can you tell why AI repeatedly credits another source?
- 04How does Delphic predict which source change is most likely to move an AI position?
- 05How should a firm decide what to change after measuring its AI position?
- 06How does Delphic prove it works before a full engagement?
5-STOP TRAIL
From market map to priority
How a mapped question becomes a governed investment decision.
- 01How does Delphic map private expertise into public question markets?
- 02How can a Knowledge Index reveal where an expert firm should expand next?
- 03How does Delphic estimate query volume for a question family?
- 04How does Delphic rank question-market opportunities?
- 05How is a Delphic engagement structured?
How AI discovery works
How is AI changing discovery and evaluation for expert firms?
A generated answer can both surface sources and frame which firms merit attention before the buyer visits a website.
READ →What does it mean when AI mentions, cites or recommends a firm?
A name, a citation, source placement and a recommendation are distinct observations; their combination reveals how AI credits the firm.
READ →Why does AI treat the same firm differently from one question to the next?
A firm can be evaluated strongly when named yet remain absent or subordinate when the buyer asks the underlying unbranded question.
READ →How can a paywalled expert firm provide evidence to AI without opening its paid product?
A paywall protects the product but cannot serve as its public evidence layer; the firm needs attributable proof outside the paid core.
READ →What should a firm audit when AI does not cite an expert source?
Audit availability, answer fit, inspectable evidence and repeated selection separately before changing the source.
READ →How much should an expert firm publish for AI without giving away what it sells?
Maximise useful non-sensitive evidence; move protected knowledge only when a measured question-market opportunity justifies the trade-off.
READ →How much can an expert firm credibly improve how AI discovers and represents it?
Potential is the per-engine, evidence-bounded gap between current position and attainable movement on each measured outcome.
READ →What can an expert firm change about how AI represents its authority?
A firm cannot rewrite inherited associations on demand; it can improve the retrievable evidence available for a specific question.
READ →Why can't one visibility score describe how AI positions a firm?
Discovery, discovery-market Authority, Brand evaluation and Competitive standing answer different commercial questions and cannot be blended.
READ →Why can't one AI answer establish a firm's position?
One answer is one variable observation; a defensible position comes from repeated evidence reported with uncertainty.
READ →The building blocks
What is a question family (and what does one look like)?
One question a firm can own, and every way buyers phrase it - the unit AI visibility is won or lost in.
READ →How should knowledge be structured to win citations?
Structure knowledge around one commercially meaningful buyer question as an Answer Object whose form, evidence and disclosure line fit that market.
READ →What is a Knowledge Index?
A firm's authority in the shape AI needs: the question map, carried by answer objects, disclosure calibrated.
READ →What public evidence makes expertise inspectable to AI?
Identity, a direct answer, visible basis, freshness and a route to depth make question-level authority inspectable.
READ →Working with Delphic
Why can't an expert firm manage AI discovery and authority as effectively in-house?
Internal execution cannot generate an independent comparative field from the firm's own portfolio alone.
READ →How is Delphic different from AEO, GEO and AIEO products and services?
AEO, GEO and AIEO approaches typically work from selected prompts and public surfaces; Delphic manages question markets derived from the firm's legitimate authority.
READ →Why does an expert firm need to keep managing how AI represents it?
Standing observation across platform, competing-supply and client-market change turns only material movement into a managed decision.
READ →What does Delphic actually do, end to end?
Each stage produces the evidence required to make the next decision - from private map through measured outcome and management.
READ →How does Delphic prove it works before a full engagement?
A bounded proof tests whether Delphic can define, measure, diagnose, treat and produce pre-agreed movement in a live question market.
READ →How do I know whether my firm is being credited by AI?
A trustworthy baseline keeps four outcomes separate, measures each engine through repeated natural questions and states uncertainty.
READ →How can you tell why AI repeatedly credits another source?
A source-gap diagnosis separates changeable evidence gaps from structural advantages, uncertainty and run variation.
READ →How does Delphic map private expertise into public question markets?
We turn what a firm knows into the buyer-question markets it can credibly own.
READ →How is a Delphic engagement structured?
Proof, private map, selected-family work and rolling management expand only when evidence and client decisions justify more scope.
READ →How should a firm decide what to change after measuring its AI position?
The defensible treatment is the smallest testable change justified by the diagnosed gap, attainable potential and approved disclosure line.
READ →How can a Knowledge Index reveal where an expert firm should expand next?
Joining demand, AI ownership, public supply, response and treatment evidence by question family reveals opportunities no signal can show alone.
READ →How does Delphic estimate query volume for a question family?
Delphic maintains a protected estimator that returns a dated, confidence-labelled query-volume estimate for one validated question family.
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READ →How does Delphic rank question-market opportunities?
Delphic maintains a protected system that turns mapped evidence into an ordered portfolio of opportunities, observations and deliberate holds.
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READ →How does Delphic predict which source change is most likely to move an AI position?
Delphic maintains a protected expected-effect system that identifies the smallest eligible source change worth testing against a measured gap.
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READ →Where this is heading
Where is expert knowledge heading in the AI economy?
Build the public evidence for today's discovery and the demand-and-supply intelligence for deciding which knowledge markets to develop tomorrow.
READ →What is an expert answer worth when AI can generate one?
As answer generation becomes abundant, value shifts toward warranted access to the authority system that can produce and stand behind decision-grade knowledge.
READ →What would it take for an AI agent to transact for expert knowledge?
Payment rails are only one layer; an expert-knowledge transaction also needs a decision need, legitimate authority, governed access rights and attributable delivery.
READ →Find the questions your firm should own.
We identify where your expertise can credibly lead, measure who AI credits today, and show the clearest opportunity to improve your position without over-disclosing what clients pay for.