Whitepaper
Architecting Agentic Systems for Accuracy and Fairness
The architectural decisions that determine whether an agentic system is accurate and fair — drawn from patterns that hold up in production rather than in demos.
Inside the paper
- Fairness as a systems property: rubrics, evaluator separation and counterfactual testing
- Governing the retrieval corpus: lineage, validity time and contradiction
- Grounding, deterministic verification and calibrated confidence
- Memory that stays an asset, not a slow accuracy leak
- Designing real human oversight, and the EU AI Act / Consumer Duty anchor
PDF · 8 pages · Gordion Solutions Insights, July 2026.