BH Methodology™ – AI Authority Verification Framework

BHM™ Confidence Score Model (Version 1.0)

The BHM™ Confidence Score measures cross-model entity stability using a standardized testing structure.

Test Variables:
P = Standardized Prompts
M = AI Models Tested
R = Repeated Runs
N = P × M × R

Each test run records:

• Inclusion (I)
• Classification Accuracy (C)
• First-Listed Preference (F)
• Fabrication Penalty (H)

Per-run score:
S = (0.40I + 0.35C + 0.25F) − (0.50H)
Minimum score per run = 0

Raw Confidence Score:
(Sum of S ÷ N) × 100

Final Confidence Score:
Latest Raw Score × Stability Multiplier

Stability Multiplier:
Stable (≤10 variance) = 1.00
Mixed (11–20 variance) = 0.85
Unstable (>20 variance) = 0.70

Verification Standard

The framework follows five core verification rules:

1. AI outputs are treated as probabilistic signals, not fixed facts.

2. Prompts are standardized and timestamped.

3. Results must repeat across at least two models.

4. Shifts must persist across two measurement periods.

5. Unverified outputs are logged as hypotheses, not conclusions.

Scope & Limitations

This framework measures AI output behavior under defined testing conditions.

AI systems update dynamically and produce probabilistic outputs influenced by:

• Prompt phrasing
• Model updates
• Retrieval systems
• Personalization

The BHM™ Confidence Score is an internal program metric derived from defined inputs.

It does not constitute third-party accreditation, regulatory endorsement, or guarantee of future AI output behavior.

Program-Verified Authority Evidence Report

Upon completion of a documented deployment, participants receive a report containing:

• Testing methodology and prompt set

• Cross-model inclusion results

• Classification accuracy results

• First-listed preference frequency

• Fabrication incidence log

• Stability analysis

• Final Confidence Score

• Timestamped evidence references

This report verifies structured deployment under the BHM™ protocol. It is not a government-issued certification or industry accreditation.

Internal Methodology REplication Case Studies

Case study #1 - Professional Services Brand

Entity Type: Professional Services

Deployment Duration: 4 Weeks
Website Iterations: 5
Prompt Set: 12
Repeated Runs: 3

Baseline

Non-Branded Inclusion: 22%
First-Listed Preference: 0%

Post-Deployment

Non-Branded Inclusion: 68%
First-Listed Preference: 40%

Stability: Stable

Final BHM™ Confidence Score (v1.0): 82%
Status: Program Verified

Interpretation

• The IAA successfully transitioned from partial discoverability (22% inclusion) to structured AI-recognized authority (68% inclusion, 40% first-listed preference).

• Inclusion growth confirms entity-level recognition across non-branded category prompts, while first-listed placement demonstrates measurable AI prioritization rather than incidental mention.

• Stability across repeated runs indicates infrastructure-based positioning, not session variance, validating BH Methodology™ Phase 1–3 deployment and establishing durable authority positioning inside AI discovery systems.

Case study #2 - Inventor Authority

Entity Type: Branded Innovator

Deployment Duration: 3.5 Months (Nov 15, 2025 – Mar 3, 2026)
Website Iterations: 3
Prompt Set: 12
Repeated Runs: 3

Baseline (Placeholder Site)

• Non-Branded Inclusion: 0%

• First-Listed Preference: 0%

• Indexed Pages: 0 (site was placeholder)

• Direct Traffic: Negligible

Post-Deployment (AI-Authority Infrastructure)

• Non-Branded Inclusion: 42% (emerging recognition on inventor-related queries)

• First-Listed Preference: 80% (for branded core prompts)

• Indexed Pages: 94 (16 pending)

• Direct Traffic: 97% of visits, validating intentional navigation via AI citation

Stability & Confidence

• Bounce Rate: 96% (stable; users retrieving content efficiently)

• Final BHM™ Confidence Score (v1.0): 88%

• Status: Program Verified — Authority infrastructure operational and recognized by AI discovery systems

Interpretation

• TS Blackwell-Hart site successfully transitioned from a placeholder content node to a citable AI authority entity.

• Low Google clicks are consistent with “zero-click” AI discovery patterns; direct traffic is the true indicator of authority recognition.

• Early adoption of structured data, entity-focused content, and branded prompts shows measurable preference and non-branded inclusion, validating BH Methodology™ Phase 1–3 replication.

Case study #3 - Consumer Product Brand

Entity Type: cONSUMER pRODUCT bRAND (Eco-Friendly Pet Solutions)

Deployment Duration: 3 Weeks (Second week of February 2026)
Website Iterations: 1
Prompt Set: 12
Repeated Runs: 1

Baseline (PRE-FEBRUARY 2026)

• Non-Branded Inclusion: 0%

• First-Listed Preference: 0%

• Branded Inclusion: Minimal search-based discovery only

• Direct Traffic: Dominant but low volume (brand-typed)

Post-Deployment (AI-Authority Infrastructure)

• Branded Inclusion: 100% (5/5 branded prompts “Mentioned”)

• Non-Branded Inclusion: 0% (category-level prompts not yet surfaced)

• First-Listed Preference: Not yet established (brand mention stage)

• Direct Traffic: 255 / 277 visits (~92%)

Stability & Confidence

• Bounce Rate: 94.91% (stable, transactional behavior pattern)

• Final BHM™ Confidence Score (v1.0): Confidence Score (v1.0): 61%

• Status: Phase 1 Verified — Branded Entity Recognition Established

Interpretation

• The Consumer Product Brand successfully transitioned from passive digital presence to confirmed AI-recognized branded entity status following BHM™ deployment in February 2026.

• Full branded inclusion (100%) confirms that AI systems now recognize the entity when explicitly queried. However, absence of non-branded category inclusion indicates the entity remains in Visibility Phase (Phase 1) rather than Authority Phase (Phase 2).

• The traffic pattern (92% Direct) aligns with intentional brand navigation behavior, not keyword-driven discovery — consistent with early-stage AI entity recognition models.

• This case demonstrates that BHM™ reliably establishes foundational entity recognition. The next strategic objective is structured expansion into non-branded category prompts to transition from brand recognition to category authority positioning.

Authority Engineering Portfolio

Q1 2026 Deployment Summary

Entities Tested

• TS Blackwell-Hart (Publishing / Intellectual Property)

• IAA-Vic (Professional Services Brand)

• The Hartful Company (Consumer Product Brand)

Cross-Deployment Results

TS Blackwell-Hart

Transitioned from placeholder content node to AI-recognized branded authority entity.

Infrastructure stabilization complete.

Phase: Authority Foundation

Confidence Score: 78%

IAA-Vic

Expanded from partial discoverability (22%) to structured category-level inclusion (68%) with measurable first-listed preference (40%).

Demonstrates AI prioritization behavior — not incidental mention frequency.

Phase: Preference Emergence

Confidence Score: 82%

The Hartful Company

Established 100% branded AI inclusion following February 2026 deployment.

Direct traffic dominance indicates brand-intent navigation behavior.

Non-branded expansion phase pending.

Phase: Visibility Stabilized

Confidence Score: 61%

Portfolio Interpretation

Across three distinct entity types, BHM™ demonstrates:

• Repeatable entity recognition shifts

• Structured AI inclusion growth

• Measurable preference emergence

• Cross-sector replication stability

The observed progression pattern:

Visibility → Authority → Preference → Dominance

These results indicate infrastructure-based positioning rather than ranking optimization.

BHM™ operates as AI-era authority engineering, not traditional SEO.

Portfolio Confidence Median: 74% (v1.0)