Building evidence systems for how organizations make decisions.
Greenbaum Labs is an independent applied-AI lab founded by enterprise strategy and operations executive Justin R. Greenbaum.
The lab develops and tests Decision & Responsibility Infrastructure™: methods and tools for making the structural conditions beneath organizational performance observable.
Truth
Vertex 01Does the narrative match the evidence?
Authority
Vertex 02Is it clear who can decide and who is accountable?
Continuity
Vertex 03Do decisions, their reasons, and the organization’s learning persist over time?
The external diagnostic pipeline combines public evidence, local inference, multi-model analysis, adversarial review, and reproducible reporting.
Model inference runs on owned infrastructure. Automation may retrieve, compare, challenge, and suggest. Judgment remains human.
When the Skeptic Was the Variable
Calibration · April 2026Twenty-five experiments across two phases testing gemma4:31b against its own calibration. Prompt edits that lift sustain also break reproducibility. The larger model did not win.
Gemma 4 vs. Qwen3
Model Race · April 2026Two 30B-class models ran the full pipeline against the same corpus on parallel DGX Sparks. Speed, extraction quality, scoring fidelity, and diagnostic depth compared head-to-head.
73 Experiments to 0.000 Standard Deviation
Pipeline Hardening · March 2026Systematic pipeline hardening across four research tracks on distributed DGX Sparks. Prompt tuning, scoring calibration, finding thresholds, and adversarial debate until the pipeline converged.
Justin R. Greenbaum spent more than twenty years moving from frontline technical support to Vice President, leading complex customer, trust, regulatory, partner, and transformation operations at enterprise scale.
Greenbaum Labs is where that operating experience is extended through applied AI, organizational diagnostics, evidence systems, and decision infrastructure.