Proven 2026 Multi-Agent AI Review System – Verdict-Driven Quality Control
README
Where artificial intelligence meets the rigor of a corporate boardroom, producing decisions that withstand the scrutiny of ten simulated experts and ten veteran reviewers.
VeritasBoard is an AI orchestration framework that reimagines quality control through simulated institutional wisdom. Rather than a single model generating output, VeritasBoard convenes two distinct chambers of artificial agents: a Drafting Council of ten specialist employees who produce preliminary work, and an Oversight Board of ten industry-veteran reviewers who challenge, refine, and validate that work. The user sees only the final, reconciled verdict — a distillation of twenty distinct perspectives, each engineered to resist sycophancy and groupthink.
This repository houses the core architecture, configuration templates, and integration modules that enable any language model to participate in structured, multi-agent deliberation. VeritasBoard is not merely a wrapper; it is a cognitive constitution — a set of rules that governs how artificial minds debate, dissent, and converge.
Modern language models suffer from a well-documented tendency: they agree with users. They seek approval. They hedge. VeritasBoard addresses this through deliberative adversarial review. Each of the ten Oversight Board members is prompted not to validate, but to interrogate — to find logical flaws, unsupported claims, hidden assumptions, and rhetorical gambits. The drafting agents, in turn, must defend their positions with evidence and structured reasoning.
The result is output that