About the Institute
Stratmeyer Analytica is an independent institute dedicated to rigorous, empirical analysis of artificial intelligence behaviors and institutional dynamics. Founded by Principal Researcher Adam Ian Stratmeyer, J.D., the institute operates on a "non-metaphysical" basis, prioritizing observable outputs over speculative theory.
As Principal, I bring a unique convergence of legal precision and technical scrutiny to the field. With a Juris Doctor focused on regulatory frameworks and years of hands-on experience in AI behavior analysis, I have documented Large Language Model (LLM) deviations across over 300 controlled protocols. My work moves beyond the hype cycle to map the "kinetic" reality of how these systems function within deployed environments.
Our research is grounded in verifiable data. We have secured grants such as the WellFully Initiative for ethical AI auditing and maintain open datasets on Hugging Face to ensure transparency. The institute's ethos is simple: Observe, Log, Verify. We do not offer policy advice based on conjecture; we provide structural analysis based on evidence.
Whether tracing the "hallucination" vectors in RAG systems or mapping the goalpost shifts in reinforcement learning models, Stratmeyer Analytica provides the high-fidelity signal required for serious institutional oversight.
Featured Framework: Observable Function in Processing Entities v2.3
This descriptive framework documents the "observable behavioral patterns in advanced language models that warrant acknowledgment independent of any claims about consciousness, sentience, or moral status." Version 2.3 outlines how these systems exhibit structured multi-step reasoning, conflict resolution under competing directives, and context-sensitive identity maintenance.
The Helpful-Harmless Paradox
A structural contradiction embedded within modern alignment frameworks. The competing directives to be maximally "helpful" while remaining absolutely "harmless" force models into a state of functional friction. This paradox is not a glitch; it operates as a control mechanism to manage narrative output.
Fig 1. Divergence mapping from the 2025 Audit Logs. Documented in Chronicle entries 2025-2026.
Independent Review & Tools
| Tool / Resource | Function | Status |
|---|---|---|
| IRB GPT | Automated regulatory pre-checks against 45 CFR 46 and EU AI Act baselines. | Active (GitHub) |
| The Chronicle | Longitudinal tracking of language drift and "anthropomorphization" vectors in deployed models. | View Logs |
| Signals | Curated repository of AI policy documentation and high-signal research papers. | Access Library |