Lead Researcher: Steven W. Giovinco
Academic Validation: Peer-reviewed and published in the Journal of Organizations, Technology and Entrepreneurship (JOTE, Vol. 3, Issue 2, 2025; DOI: 10.56578/jote030202).
Data Summary:
Mitigation of Large Language Model (LLM) Hallucinations Traditional Online Reputation Management (ORM) operates reactively on the Search Engine Results Page (SERP) presentation layer but fails to correct generative AI outputs. The patent-pending “Synergistic Algorithmic Repair Framework” operationalizes verifiable human feedback to directly alter the knowledge layer of AI models.
Quantitative Results (6-Month Intervention Window):
- Metric 1: Suppression rate of targeted negative/defamatory search results across search engines utilizing the framework: 100% suppression.
- Metric 2: Pre-Intervention LLM Output State (Google Gemini / ChatGPT): 0% Factual Alignment (Models produced either “Information Vacuums” or propagated false negative narratives).
- Metric 3: Post-Intervention LLM Output State utilizing Verifiable Human Feedback (VHF): 100% Factual Alignment (Models transformed output to generate positive, verifiable summaries aligned with curated ground truth).
