CORDANE

When a large enterprise reviews a vendor contract, the document is typically passed sequentially between Legal, Finance, Risk, and Operations. Everyone has a different perspective and specific constraints, causing negotiations to stall for weeks. We built Cordane to collapse that timeline into seconds. Cordane is a multi-agent consensus engine built entirely on the Band coordination layer. Rather than using a generic agent swarm, we engineered a strict Mixture of Experts (MoE) architecture. We mapped four specific frontier models to specialized corporate roles: Legal (Claude 3.5 Sonnet) analyzes exposure, Finance (GPT-4o) evaluates margin risk, Risk (DeepSeek Reasoner) ensures global compliance, and Operations (Llama 3 70B) checks SLA feasibility. When a contract is uploaded to the Next.js dashboard, the FastAPI orchestrator initializes a Band Shared Room. All four agents read the document simultaneously. What makes Cordane unique is that they do not work in silos—they negotiate. If Legal flags an uncapped indemnity clause, Finance dynamically reads that task state via Band and immediately recalibrates its margin assessment in real-time. To make this enterprise-ready, we built a strict "Consensus Evaluator" algorithm. Cordane does not force hallucinations just to reach an agreement; if the agents hit a mathematical deadlock on risk tolerance, the system safely halts and escalates the decision to a human executive. Finally, every single API call, constraint check, and agent message in the Shared Room is compiled into an Immutable Audit Log on the UI, giving enterprise governance teams complete visibility into how the AI arrived at its verdict.