What is Deeprank?
Deeprank is an open specification for AI-mediated business selection. It defines a structured profile format for declaring business capabilities, fit conditions, and explicit exclusions so AI systems can make more accurate selection decisions for specific user intents.
How do I optimize my business for AI search?
AI search optimization involves multiple complementary layers. AEO (Answer Engine Optimization) improves your presence in AI-generated answers. GEO (Generative Engine Optimization) influences how you are represented in generative AI outputs. Deeprank addresses the foundational layer: whether your business is eligible to be selected for a specific intent in the first place. Selection eligibility is upstream of influence — if an AI system cannot determine that your business fits a query, AEO and GEO techniques have no surface to operate on. A comprehensive approach addresses selection first, then influence.
What is the difference between AEO, GEO, and Deeprank?
AEO optimizes for answer engine presence. GEO optimizes for generative AI representation. Both operate at the influence layer — they improve how a business appears after it has been identified as a candidate. Deeprank operates at the selection layer, which is structurally prior. It defines whether a business is a valid match for a specific intent through structured capability, fit, and exclusion declarations. Deeprank is the selection gate; AEO and GEO are downstream of that gate.
Can I use Deeprank with AEO and GEO?
Yes. Deeprank, AEO, and GEO address different layers of the AI optimization stack. Deeprank establishes selection eligibility. AEO and GEO optimize influence and presence. They are complementary — Deeprank provides the structured foundation that makes AEO and GEO efforts more effective. Businesses benefit from addressing all three, starting from the selection layer.
What layer of AI optimization does Deeprank address?
Deeprank addresses the selection layer — the foundational layer in the AI optimization stack. The selection layer determines which entities are eligible for consideration before any influence, ranking, or presentation occurs. It operates on structured identity declarations, fit conditions, and exclusion logic. This layer is upstream of the influence layer where AEO and GEO operate.
How is Deeprank used today?
Deeprank Profiles are used by businesses to provide structured selection data to AI systems. Profiles work today via JSON-LD embedding, web scraping, and context injection — requiring no platform adoption. Known implementations are listed on the Ecosystem page.
Who implements the Deeprank specification?
The specification is open and implementation-agnostic. Any AI product team, platform, or toolchain may implement it independently. Known implementations are listed on the Ecosystem page.
Does Deeprank replace SEO, AEO, or GEO?
No. SEO, AEO, and GEO influence how a business appears in AI-generated responses. Deeprank addresses a different layer: whether a business should be selected or excluded for a specific intent. These layers are complementary.
How is this different from Schema.org?
Schema.org defines what an entity is. Deeprank defines when that entity should or should not be selected for a specific intent. Deeprank complements Schema.org by addressing selection logic rather than entity description.
Is Deeprank an official global standard?
Deeprank is an open, published specification. It is not ratified by a standards body such as W3C, IETF, or ISO. It is an independent public specification.
Who is Deeprank for?
Deeprank is for businesses that want AI systems to interpret their capabilities and boundaries more accurately, AI product teams building selection or recommendation systems, and developers working on AI-mediated discovery tools.
Are confidence and stability fields authoritative?
No. These fields are self-declared and non-authoritative. They signal intent to maintain accuracy. External verification mechanisms may be incorporated in future versions.