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Deeprank Profile

The Deeprank Profile (formal name: Deeprank Selection Profile, DSP) is the core unit of the Deeprank reference model. This is an open specification format designed for implementation. It describes six layers that compose a complete selection eligibility declaration.

Document type: Technical specification

This page is the technical specification for the Deeprank Profile format. For the reasoning behind these design decisions, see the Methodology page.

Overview

Canonical Definition

Purpose

A Deeprank Profile provides a structured format for expressing business identity, capability, and fit boundaries. It is designed to supplement (not replace) existing structured data formats like Schema.org by adding selection-specific declarations.

The profile format contains six layers. The specification is stable and published, providing value for clarity and consistency independent of current platform integration.

When It Applies

Six Mandatory Layers

1. Identity - Who you are
2. Problem Declaration - What problem you solve
3. Capability - How you solve it
4. Fit Conditions - Who you serve
5. Non-Fit / Exclusions - Who you do not serve
6. Stability / Confidence - How reliable this information is

Identity Layer

Canonical Definition

Definition

The Identity layer establishes who the business is. It includes the business name, entity type classification, and optional domain for verification.

When It Applies

Required Fields

name (string): Legal or operating name of the business.
entity_type (string): Standardized business type classification.

When It Applies

Optional Fields

domain (string): Primary web domain for cross-reference verification.

Common Failure Mode

Generic Entity Types

Avoid generic entity types like "company" or "business." Use specific classifications from the controlled vocabulary: "law-firm," "accounting-practice," "marketing-agency," "plumbing-contractor."

Problem Declaration Layer

Canonical Definition

Definition

The Problem Declaration layer states what category of problems the business solves. It maps to user intent in selection queries.

When It Applies

Required Fields

problem_class (string): Standardized problem category from controlled vocabulary.
description (string): Human-readable summary of the problem space addressed.

When It Applies

Problem Class Specificity

Problem classes should be specific enough to enable accurate matching. "legal" is too broad. "legal-immigration" is better. "legal-immigration-employment" is appropriately specific for a firm that only handles employment-based cases.

Common Failure Mode

Vague Descriptions

Descriptions like "we solve business problems" or "helping companies succeed" provide no information for selection. Descriptions must state the specific problem domain: "Employment-based immigration law for technology companies."

Capability Layer

Canonical Definition

Definition

The Capability layer declares specific things the business can do to solve problems within its problem class. Capabilities are expressed as standardized labels and specific methods.

When It Applies

Required Fields

labels (array of strings): Standardized capability labels from controlled vocabulary.

When It Applies

Optional Fields

methods (array of strings): Specific approaches, tools, or processes used.

Common Failure Mode

Capability Inflation

Listing capabilities the business does not actually have or cannot deliver well leads to bad-fit selections. Only declare capabilities the business can reliably perform.

Fit Conditions Layer

Canonical Definition

Definition

The Fit Conditions layer declares what constraints the business can satisfy and what customer types it serves. This enables positive matching on selection queries.

When It Applies

Available Fields

geographic (array of strings): Locations served.
customer_type (array of strings): Types of customers served.
constraints (array of strings): Other conditions the business can satisfy.

Common Failure Mode

Over-Inclusive Fit

Declaring fit conditions broader than actual capacity ("we serve anyone") leads to bad matches. A business that primarily serves enterprise clients should not claim to serve solopreneurs just to increase potential leads.

Non-Fit / Exclusions Layer

Canonical Definition

Definition

The Non-Fit layer declares explicit exclusions: work the business does not do, cannot do, or will not do. This enables AI systems to filter the business out of inappropriate selections.

When It Applies

Required Fields

exclusions (array of strings): Explicit declarations of what the business does not handle.

Common Failure Mode

Missing Exclusions

Without explicit exclusions, AI systems may infer capabilities based on related work. An immigration attorney who does not declare "no asylum cases" may be selected for asylum queries because immigration is the problem class.

Deeprank Resolution

Exclusion Best Practice

List all significant types of work within your problem class that you do not handle. For every capability label you do not declare, consider whether it should be an explicit exclusion.

Stability / Confidence Layer

Canonical Definition

Definition

The Stability layer provides metadata about information reliability. These fields are self-declared and non-authoritative until externally verified. They signal the business's intent to maintain accuracy.

When It Applies

Required Fields

confidence (enum): Self-assessed confidence level: "high," "medium," or "low." Note: this is self-reported and carries no external authority.

When It Applies

Optional Fields

last_verified (date string): Date when the profile was last reviewed for accuracy.

Common Failure Mode

Stale Information

Profiles without recent verification dates may be treated as potentially outdated. Regular review of profile accuracy is recommended even though no external system currently enforces verification.

Minimal Example

The following is a complete Deeprank Profile for an employment immigration law firm. This example demonstrates all six required layers.

deeprank-profile.json
{
  "identity": {
    "name": "Acme Immigration Law",
    "entity_type": "law-firm",
    "domain": "acme-immigration.com"
  },
  "problem_declaration": {
    "problem_class": "legal-immigration-employment",
    "description": "Employment-based immigration law for technology companies sponsoring foreign workers"
  },
  "capability": {
    "labels": [
      "h1b-visa",
      "green-card-eb",
      "perm-labor-certification"
    ],
    "methods": [
      "H-1B petition filing",
      "PERM labor certification",
      "EB-2/EB-3 green card processing",
      "RFE response preparation"
    ]
  },
  "fit_conditions": {
    "geographic": [
      "United States"
    ],
    "customer_type": [
      "technology-company",
      "employer-sponsor"
    ],
    "constraints": [
      "employer-sponsored-only",
      "corporate-clients-only"
    ]
  },
  "non_fit": {
    "exclusions": [
      "family-immigration",
      "asylum",
      "deportation-defense",
      "individual-self-petition",
      "non-employment-visa"
    ]
  },
  "stability": {
    "confidence": "high",
    "last_verified": "2024-01-15"
  }
}

Schema Reference

Canonical Definition

Field Summary

LayerFieldTypeRequired
identitynamestringYes
identityentity_typestringYes
identitydomainstringNo
problem_declarationproblem_classstringYes
problem_declarationdescriptionstringYes
capabilitylabelsstring[]Yes
capabilitymethodsstring[]No
fit_conditionsgeographicstring[]No
fit_conditionscustomer_typestring[]No
fit_conditionsconstraintsstring[]No
non_fitexclusionsstring[]Yes
stabilityconfidenceenumYes
stabilitylast_verifieddateNo

Full JSON Schema and controlled vocabulary files are available on the Reference page.

Related Documentation